Method and system for assigning order, and computer-readable recording medium

Abstract

The present disclosure relates to a method and a system for assigning an order. The method for assigning an order may comprise the steps of: obtaining information about a delivery order; identifying information about working conditions of a delivery person; obtaining information about a reference time provided to a customer having requested the delivery order; on the basis of the information about the delivery order and the information about the working conditions, generating information about a predicted time according to the delivery person performing the delivery order and information about a threshold time used for comparing the reference time to the predicted time; and, on the basis of the reference time, the predicted time and the threshold time, determining whether to assign the delivery order to the delivery person.

Description

Method of assigning orders, system, and computer-readable recording medium

[0001] The present disclosure relates to a method and system for assigning orders.

[0002] Due to the recent rapid growth of e-commerce and mobile platforms, the demand for order-based delivery services is increasing significantly across various sectors. As the delivery of goods and services used daily by consumers—such as food, fresh produce, and household items—becomes more active, the technological requirements for efficient order management and rapid delivery are rising.

[0003] Existing order assignment systems have primarily utilized simple distance-based or first-come, first-served methods. However, these approaches may fail to adequately account for the complex situations encountered in actual delivery environments, such as the delivery driver's current workload, traffic conditions, and the characteristics of the mode of transportation. Furthermore, such methods may be difficult to apply in complex situations where multiple orders need to be processed simultaneously or where multiple customers and drivers must be efficiently matched.

[0004] The present disclosure provides a method and system for allocating orders to solve the above-mentioned problems.

[0005] The present disclosure may be implemented in various ways, including a method, an apparatus (system), or a computer program stored on a readable storage medium.

[0006] According to one embodiment of the present disclosure, an order assignment method may include the steps of obtaining information about a delivery order, identifying information about a delivery worker's work conditions, obtaining information about a reference time provided to a customer who requested the delivery order, generating information about a predicted time for the delivery worker to perform the delivery order and information about a threshold time used for comparison between the reference time and the predicted time based on the information about the delivery order and the information about the work conditions, and determining whether to assign the delivery order to the delivery worker based on the reference time, the predicted time, and the threshold time.

[0007] According to one embodiment of the present disclosure, information regarding work conditions may include information associated with at least one of the delivery status of a delivery worker or the means of transportation of a delivery worker.

[0008] According to one embodiment of the present disclosure, the generating step may include the step of generating information about an expected route for a delivery person to perform a delivery order based on information about a delivery order and information about business conditions.

[0009] According to one embodiment of the present disclosure, information regarding a delivery order may include information regarding the delivery type of the delivery order.

[0010] According to one embodiment of the present disclosure, the step of generating information about an expected route may include generating information about a sub-delivery type of a delivery order based on information about a delivery type and information about business conditions, and generating information about an expected route based further on information about a sub-delivery type.

[0011] According to one embodiment of the present disclosure, a delivery order is associated with at least one order, and the step of generating may further include the step of generating information about a residual path for each of at least one order as at least a part of the expected path based on information about an expected path, and the step of generating information about a predicted time for each of at least one order based on information about the residual path.

[0012] According to one embodiment of the present disclosure, the generating step may further include the step of generating information about a threshold time for each of at least one order based on information about a residual path.

[0013] According to one embodiment of the present disclosure, information regarding a delivery order includes information regarding the delivery type of the delivery order, and the step of generating may include the step of generating information regarding a threshold time based on the information regarding the delivery type.

[0014] According to one embodiment of the present disclosure, information regarding a delivery order includes information regarding the delivery type of the delivery order, and the step of generating may include the step of generating information regarding the sub-delivery type of the delivery order based on information regarding the delivery type and information regarding business conditions, and the step of generating information regarding the critical time based on information regarding the sub-delivery type.

[0015] According to one embodiment of the present disclosure, the method further comprises the step of obtaining information about a delivery order and information about a target condition associated with information about a work condition, and the generating step may include the step of determining whether the information about the delivery order and the information about the work condition satisfy the target condition, and the step of determining a threshold time as a predetermined time based on the determination result.

[0016] According to one embodiment of the present disclosure, the step of determining whether to assign a delivery order to a delivery person may include the step of determining whether to assign the delivery order to a delivery person based on the comparison of the sum of the predicted time and the threshold time and the reference time.

[0017] According to one embodiment of the present disclosure, the step of determining whether to assign to a delivery person based on a comparison of the sum of the predicted time and the threshold time and a reference time may include a step of determining not to assign the delivery order to the delivery person if the sum of the predicted time and the threshold time is greater than the reference time, or a step of determining to assign the delivery order to the delivery person if the sum of the predicted time and the threshold time is less than or equal to the reference time.

[0018] According to one embodiment of the present disclosure, a delivery order is associated with a first order and a second order, and the step of obtaining information about a reference time includes obtaining information about a first reference time associated with the first order and information about a second reference time associated with the second order, and the step of generating may include obtaining information about a first prediction time associated with the first order, information about a first threshold time, information about a second prediction time associated with the second order, and information about a second threshold time.

[0019] According to one embodiment of the present disclosure, the step of determining whether to assign a delivery order to a delivery person may include determining whether to assign the delivery order to a delivery person based on at least one of a comparison between the sum of a first prediction time and a first threshold time and a first reference time or a comparison between the sum of a second prediction time and a second threshold time and a second reference time.

[0020] According to one embodiment of the present disclosure, a computer-readable recording medium may record instructions for executing at least one of the methods described above on a computer.

[0021] According to one embodiment of the present disclosure, an information processing system comprises a memory and at least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory, and the at least one program may include instructions for obtaining information about a delivery order, identifying information about a delivery worker's work conditions, obtaining information about a reference time provided to a customer who requested the delivery order, generating information about a predicted time for the delivery worker to perform the delivery order and information about a threshold time used for comparison between the reference time and the predicted time based on the information about the delivery order and the information about the work conditions, and determining whether to assign the delivery order to the delivery worker based on the reference time, the predicted time, and the threshold time.

[0022] According to various embodiments of the present disclosure, the customer's user experience can be further improved by receiving the ordered food and / or goods within a time close to the reference time.

[0023] According to various embodiments of the present disclosure, the user experience for the delivery person can be further improved by having the delivery person perform more delivery tasks via an optimal route.

[0024] The effects of the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art to which the present disclosure pertains (referred to as "person skilled in the art") from the description in the claims.

[0025] Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, wherein similar reference numerals indicate similar elements, but are not limited thereto.

[0026] FIG. 1 is a flowchart illustrating an example of a method for assigning orders according to one embodiment of the present disclosure.

[0027] FIG. 2 is a schematic diagram showing a configuration in which an information processing system for assigning orders according to one embodiment of the present disclosure is connected to communicate with a plurality of user terminals.

[0028] FIG. 3 is a block diagram showing the internal configuration of a user terminal and an information processing system according to one embodiment of the present disclosure.

[0029] FIG. 4 is a flowchart illustrating an example of a step for generating information about a predicted time and information about a threshold time according to one embodiment of the present disclosure.

[0030] FIG. 5 is a diagram illustrating a method for generating information about a residual path according to one embodiment of the present disclosure.

[0031] FIG. 6 is a drawing showing an example of at least one case according to one embodiment of the present disclosure.

[0032] FIG. 7 is a drawing illustrating an example of at least one situation according to one embodiment of the present disclosure.

[0033] FIG. 8 is a drawing showing an example of at least one case according to one embodiment of the present disclosure.

[0034] FIG. 9 is a drawing illustrating an example of at least one situation according to one embodiment of the present disclosure.

[0035] FIG. 10 is a flowchart illustrating an example of a method for assigning a delivery order to a delivery person according to one embodiment of the present disclosure.

[0036] FIG. 11 is a flowchart illustrating an example of a method for assigning a delivery order to a delivery person according to one embodiment of the present disclosure.

[0037] Hereinafter, specific details for implementing the present disclosure will be described in detail with reference to the attached drawings. However, in the following description, specific descriptions regarding well-known functions or configurations will be omitted if there is a risk that the gist of the present disclosure may be unnecessarily obscured.

[0038] In the attached drawings, identical or corresponding components are assigned the same reference numerals. Additionally, in the description of the following embodiments, the description of identical or corresponding components may be omitted. However, even if a description of a component is omitted, it is not intended that such component is not included in any embodiment.

[0039] The advantages and features of the disclosed embodiments and the methods for achieving them will become clear by referring to the embodiments described below in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms, and the embodiments provided are merely to make the present disclosure complete and to fully inform those skilled in the art of the scope of the invention.

[0040] The terms used in this specification will be briefly explained, and the disclosed embodiments will be described in detail. The terms used in this specification have been selected to be as generally used as possible, taking into account their functions in this disclosure; however, these terms may vary depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Additionally, in specific cases, terms may be arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the relevant description of the invention. Therefore, the terms used in this disclosure should be defined not merely by their names, but based on their meanings and the content throughout this disclosure.

[0041] In this specification, singular expressions include plural expressions unless the context clearly specifies them as singular. Additionally, plural expressions include singular expressions unless the context clearly specifies them as plural. Throughout the specification, when a part is described as including a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0042] Additionally, the terms 'module' or 'part' as used in the specification refer to software or hardware components, and the 'module' or 'part' performs certain roles. However, the meaning of 'module' or 'part' is not limited to software or hardware. The 'module' or 'part' may be configured to reside in an addressable storage medium or configured to run on one or more processors. Thus, as an example, the 'module' or 'part' may include components such as software components, object-oriented software components, class components, and task components, and at least one of processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, or variables. The components and the functions provided within the 'module' or 'part' may be combined into a smaller number of components and 'modules' or 'parts', or further separated into additional components and 'modules' or 'parts'.

[0043] According to one embodiment of the present disclosure, a ‘module’ or ‘part’ may be implemented as a processor and memory. The term ‘processor’ should be broadly interpreted to include a general-purpose processor, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a controller, a microcontroller, a state machine, etc. In some environments, the term ‘processor’ may refer to an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), etc. The term ‘processor’ may also refer to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of multiple microprocessors, a combination of one or more microprocessors combined with a DSP core, or any other combination of such configurations. Additionally, the term ‘memory’ should be broadly interpreted to include any electronic component capable of storing electronic information. 'Memory' may refer to various types of processor-readable media, such as Random Access Memory (RAM), Read-Only Memory (ROM), Non-Volatile Random Access Memory (NVRAM), Programmable Read-Only Memory (PROM), Erasable-Programmable Read-Only Memory (EPROM), Electrically Erasable PROM (EEPROM), Flash Memory, Magnetic or Optical Data Storage Devices, Registers, etc. If a processor can read information from memory and / or write information to memory, the memory is said to be in an electronic communication state with the processor. Memory integrated into a processor is in an electronic communication state with the processor.

[0044] In the present disclosure, the 'system' may include at least one of a server device and a cloud device, but is not limited thereto. For example, the system may be composed of one or more server devices. As another example, the system may be composed of one or more cloud devices. As yet another example, the system may be configured and operated with both a server device and a cloud device.

[0045] In the present disclosure, 'display' may refer to any display device associated with a computing device, for example, any display device capable of displaying any information / data controlled by or provided by the computing device.

[0046] In the present disclosure, 'each of a plurality of A' or 'each of a plurality of A' may refer to each of all components included in a plurality of A, or each of some components included in a plurality of A.

[0047] In the present disclosure, 'user' may refer to a user utilizing the application or a user account of the application. Here, a user account may represent an account created and utilized by the user within the application or data associated therewith.

[0048] Various embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. The size or location of display screens, images, buttons, etc., as illustrated and described in the drawings are exemplary and are not limited thereto. For example, some buttons may be added or omitted, or configured with sizes and locations different from those illustrated. Furthermore, the flowcharts and descriptions illustrated in the drawings are merely examples and may be implemented differently in some embodiments. For example, one or more steps may be omitted, the order of each step may be changed, one or more steps may be performed in overlap, or one or more steps may be performed repeatedly.

[0049] FIG. 1 is a flowchart (100) showing an example of a method for assigning orders according to one embodiment of the present disclosure.

[0050] The user may use an application installed on the user terminal (e.g., an application providing a service for assigning orders). The user terminal may transmit and receive data and / or information to and from an information processing system that provides a service for assigning orders through the application. The service provided by the application described below may be a complex service that integrates e-commerce services, content streaming services, food delivery services, etc. Additionally, the service provided by the application may include a service for assigning orders. The configuration of the user terminal and the information processing system will be described in detail with reference to FIGS. 2 and 3.

[0051] A customer can request an order using an application through a user terminal. An information processing system can receive information regarding an order from the user terminal. The information processing system can generate information regarding a delivery order by forming at least one order into a single bundle.

[0052] The information processing system can obtain information regarding a delivery order from a user terminal. The information processing system can assign a delivery order to a delivery person using an order assignment method. The delivery person assigned the delivery order performs the tasks related to the delivery order, and the customer can receive goods and / or services corresponding to the delivery order.

[0053] A method for assigning an order may be performed by a processor (e.g., at least one processor included in a user terminal and / or information processing system). A method for assigning an order may be initiated by obtaining information about a delivery order (S110).

[0054] In one embodiment, a delivery order may be associated with a single order or multiple orders. Here, a single order may represent a process in which a delivery person picks up a delivery target at a single pickup location and drops off a delivery target at a single drop-off location. Multiple orders may have a sequence relative to each other. For example, a first order included in multiple orders may be executed prior to a second order included in multiple orders.

[0055] In one embodiment, information regarding a delivery order may include information regarding the delivery type of the delivery order. Information regarding the delivery type may include information associated with a plurality of orders. For example, information regarding the delivery type may include the number of orders, the order of orders, etc. For example, a delivery order may be determined such that a second order is executed after a first order. Information regarding the delivery type may include information indicating that a second order must be executed after the first order.

[0056] In one embodiment, information regarding a delivery order may include information regarding a location associated with the order. For example, it may include information regarding a pickup location and a drop-off location associated with at least one order corresponding to the delivery order.

[0057] In one embodiment, the delivery type of a delivery order may include, but is not limited to, a first delivery type through a fifth delivery type. A first delivery type may correspond to one order. A second delivery type may correspond to two orders. In a second delivery type, the order of the two orders may not be predetermined. A third delivery type may correspond to three orders. A fourth delivery type may correspond to two orders. In a fourth delivery type, the order of the two orders may be predetermined. A fifth delivery type may correspond to two first orders and one second order. In a fifth delivery type, the order of the two first orders is not determined relative to each other, but it may be determined that the first order is executed before the second order. Alternatively, it may be determined that the second order is executed before the first order. The delivery type of a delivery order is predetermined and may be determined in various ways for at least one order.

[0058] In one embodiment, the processor can identify information regarding the delivery worker's work conditions (S120). For example, the information regarding the work conditions may include information associated with at least one of the delivery worker's delivery status or the delivery worker's means of transportation. For example, the information associated with the delivery status may include information regarding the delivery worker's current location, whether a delivery order is currently being executed, the type of delivery order currently being executed, whether the delivery order can be received, etc.

[0059] In one embodiment, information associated with a means of transportation may include information regarding the means of transportation used by a delivery person for a delivery order. For example, information associated with a means of transportation may be predetermined. Information associated with a means of transportation may include information associated with a first to fourth means of transportation. For example, the first means of transportation may correspond to a vehicle. The second means of transportation may correspond to a motorcycle. The third means of transportation may correspond to a bicycle. The fourth means of transportation may correspond to walking. The four means of transportation described above are merely examples, and information associated with a means of transportation may be determined in various ways.

[0060] In one embodiment, the processor may obtain information regarding a reference time provided to a customer who has requested a delivery order (S130). The information regarding the reference time may be information provided to the customer. For example, the information regarding the reference time may be information provided to the customer as the estimated arrival time of the order.

[0061] In one embodiment, when a delivery order is associated with multiple orders, a reference time may be calculated for each order. For example, a first reference time may be calculated for a first order, and information regarding the first reference time may be provided to the customer. A second reference time may be calculated for a second order, and information regarding the second reference time may be provided to the customer. The customer receiving information regarding the first reference time and the customer receiving information regarding the second reference time may be the same or different.

[0062] In one embodiment, the processor can generate information about the predicted time for a delivery person to perform a delivery order and information about a threshold time used to compare the reference time and the predicted time, based on information about a delivery order and information about work conditions (S140).

[0063] In one embodiment, the processor may generate information regarding an expected route for a delivery person to perform a delivery order based on information regarding a delivery order and information regarding work conditions. The expected route may correspond to the route for performing a delivery order when the delivery person is assigned a delivery order. Specifically, the processor may generate information regarding a sub-delivery type of a delivery order based on information regarding a delivery type and information regarding work conditions. Subsequently, information regarding an expected route may be generated based further on the information regarding the sub-delivery type. A method for generating an expected route is described in detail with reference to FIG. 4.

[0064] In one embodiment, a sub-delivery type may correspond to a delivery type. For example, a delivery type may include a first delivery type and a second delivery type. A sub-delivery type may include at least one first sub-delivery type for the first delivery type. A sub-delivery type may include at least one second sub-delivery type for the second delivery type.

[0065] In one embodiment, a sub-delivery type may be determined based on information regarding the delivery worker's work conditions. For example, the processor may determine a first_1 sub-delivery type in a first delivery type in response to identifying information in the information regarding the delivery worker's work conditions indicating that the delivery worker is not currently making a delivery. The processor may determine a first_2 sub-delivery type in a first delivery type in response to identifying information in the information regarding the delivery worker's work conditions indicating that the delivery worker is currently making a delivery. Additionally, the processor may determine a second_1 sub-delivery type in a second delivery type in response to identifying information in the information regarding the delivery worker's work conditions indicating that the delivery worker is not currently making a delivery. The processor may determine a second_2 sub-delivery type in a second delivery type in response to identifying information in the information regarding the delivery worker's work conditions indicating that the delivery worker is currently making a delivery. Examples of sub-delivery types are described in detail with reference to FIGS. 6 through 9.

[0066] In one embodiment, the processor may generate information about a residual path for each of at least one order as at least a part of the expected path, based on information about an expected path. Based on information about the residual path, the processor may generate information about a predicted time for each of at least one order. A method for generating information about the residual path and information about the predicted time is described in detail with reference to FIG. 5.

[0067] In one embodiment, the processor may generate information regarding a threshold time for each of at least one order based on information regarding a remaining path. The processor may further generate information regarding a threshold time based on information regarding a delivery type. The processor may further generate information regarding a threshold time based on information regarding a sub-delivery type. A method for calculating the threshold time will be described in detail with reference to FIGS. 6 through 9.

[0068] In one embodiment, the processor may include information regarding a delivery order and information regarding a target condition associated with information regarding a business condition. The processor may determine whether the information regarding the delivery order and the information regarding the business condition satisfy the target condition. Subsequently, based on the determination result, the processor may determine a threshold time as a predetermined time.

[0069] In one embodiment, the method for calculating the reference time and the predicted time may differ. In one example, the reference time may be calculated before the delivery order is assigned to a delivery person. For example, the reference time may be calculated statistically based on information such as the pickup and drop-off locations of the order. In one example, the predicted time may be calculated based on information regarding the delivery order. The predicted time may be calculated on the premise that the delivery order is assigned to a delivery person. For example, a delivery order may be associated with at least one order. The processor may calculate an expected route for at least one order and calculate a predicted time for each of the at least one order.

[0070] In one embodiment, the processor may determine whether to assign a delivery order to a delivery person based on a reference time, a predicted time, and a threshold time (S150). For example, the processor may determine whether to assign a delivery order to a delivery person based on a comparison of the sum of the predicted time and the threshold time with the reference time. For example, the processor may decide not to assign the delivery order to a delivery person if the sum of the predicted time and the threshold time is greater than the reference time. Alternatively, the processor may decide to assign the delivery order to a delivery person if the sum of the predicted time and the threshold time is less than or equal to the reference time.

[0071] In one embodiment, a delivery order may be associated with a first order and a second order. A processor may obtain information regarding a first reference time associated with the first order and information regarding a second reference time associated with the second order. A processor may obtain information regarding a first prediction time associated with the first order, information regarding a first threshold time, information regarding a second prediction time associated with the second order, and information regarding a second threshold time. For example, a processor may determine whether to assign a delivery order to a delivery person based on at least one of a comparison between the sum of the first prediction time and the first threshold time and the first reference time, or a comparison between the sum of the second prediction time and the second threshold time and the second reference time.

[0072] In one embodiment, the processor may determine to assign it to a delivery person. The processor may transmit information regarding the delivery order to a user terminal associated with the delivery person. The delivery person may verify the information regarding the delivery order and perform the delivery order.

[0073] In another embodiment, the processor may decide not to assign to a delivery person. The processor may perform the order assignment method of the present disclosure again for that delivery person and other delivery persons. The processor may repeat the order assignment method of the present disclosure until a delivery order is assigned to a delivery person. If there are no longer any delivery persons to perform the order assignment method of the present disclosure, the processor may determine that the assignment of the delivery order to the delivery person has failed. Thus, after the step (S150) of determining whether to assign a delivery order to a delivery person, the processor may perform various processes based on the result of the determination.

[0074] FIG. 2 is a schematic diagram showing a configuration in which an information processing system (230) for assigning orders according to one embodiment of the present disclosure is connected to communicate with a plurality of user terminals (210_1, 210_2, 210_3). As illustrated, the plurality of user terminals (210_1, 210_2, 210_3) may be connected to an information processing system (230) capable of providing a service for assigning orders through a network (220). Here, the plurality of user terminals (210_1, 210_2, 210_3) may include user terminals that receive a service for assigning orders. For example, the plurality of user terminals (210_1, 210_2, 210_3) may include a user terminal of a customer who requested an order or a user terminal of a delivery person who is the target of order assignment.

[0075] In one embodiment, the information processing system (230) may include one or more server devices and / or databases capable of storing, providing, and executing computer-executable programs (e.g., downloadable applications) and data associated with the provision of services for allocating orders, or one or more distributed computing devices and / or distributed databases based on cloud computing services.

[0076] The order assignment service provided by the information processing system (230) may be provided to the user through an order assignment service application, a web browser, a web browser extension, etc. installed on each of the multiple user terminals (210_1, 210_2, 210_3). For example, the information processing system (230) may provide information corresponding to an order assignment request, etc. received from the user terminals (210_1, 210_2, 210_3) through an order assignment service application, etc., or perform corresponding processing.

[0077] Multiple user terminals (210_1, 210_2, 210_3) can communicate with an information processing system (230) through a network (220). The network (220) can be configured to enable communication between the multiple user terminals (210_1, 210_2, 210_3) and the information processing system (230). Depending on the installation environment, the network (220) may be configured as a wired network such as Ethernet, Power Line Communication, telephone line communication devices and RS-serial communication, a mobile communication network, a Wireless LAN (WLAN), Wi-Fi, Bluetooth and ZigBee, or a combination thereof. The communication method is not limited and may include not only communication methods utilizing communication networks that the network (220) may include (e.g., mobile communication network, wired internet, wireless internet, broadcasting network, satellite network, etc.) but also short-range wireless communication between user terminals (210_1, 210_2, 210_3).

[0078] In FIG. 2, a mobile phone terminal (210_1), a tablet terminal (210_2), and a PC terminal (210_3) are illustrated as examples of user terminals, but are not limited thereto. The user terminals (210_1, 210_2, 210_3) may be any computing device capable of wired and / or wireless communication and capable of installing and running applications for services that assign orders or web browsers, etc. For example, user terminals may include an AI speaker, a smartphone, a mobile phone, a navigation system, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, a game console, a wearable device, an IoT (Internet of Things) device, a VR (Virtual Reality) device, an AR (Augmented Reality) device, a set-top box, etc. Additionally, FIG. 2 illustrates three user terminals (210_1, 210_2, 210_3) communicating with an information processing system (230) through a network (220), but is not limited thereto, and may be configured so that a different number of user terminals communicate with an information processing system (230) through a network (220).

[0079] In FIG. 2, a configuration in which a user's request (e.g., an order assignment request, etc.) is transmitted to an information processing system (230) through a user terminal (210_1, 210_2, 210_3) is illustrated as an example, but is not limited thereto. A user's request may be provided to an information processing system (230) through an input device associated with the information processing system (230) without passing through the user terminal (210_1, 210_2, 210_3), and a result of processing the user's request (e.g., information that an order has been assigned to a delivery person, etc.) may be provided to the user through an output device associated with the information processing system (230) (e.g., a display, etc.).

[0080] FIG. 3 is a block diagram showing the internal configuration of a user terminal (210) and an information processing system (230) according to an embodiment of the present disclosure. The user terminal (210) may refer to any computing device capable of running applications, web browsers, etc., and capable of wired / wireless communication, and may include, for example, the mobile phone terminal (210_1), tablet terminal (210_2), PC terminal (210_3) of FIG. 2. As shown in FIG. 3, the user terminal (210) may include a memory (312), a processor (314), a communication module (316), and an input / output interface (318). Similarly, the information processing system (230) may include a memory (332), a processor (334), a communication module (336), and an input / output interface (338). As illustrated in FIG. 3, the user terminal (210) and the information processing system (230) may be configured to communicate information and / or data through the network (220) using their respective communication modules (316, 336). Additionally, the input / output device (320) may be configured to input information and / or data to the user terminal (210) or output information and / or data generated from the user terminal (210) through the input / output interface (318).

[0081] The memory (312, 332) may include any non-transient computer-readable recording medium. According to one embodiment, the memory (312, 332) may include a permanent mass storage device such as ROM (read-only memory), a disk drive, a solid-state drive (SSD), or flash memory. As another example, a permanent mass storage device such as ROM, an SSD, flash memory, or a disk drive may be included in the user terminal (210) or information processing system (230) as a separate permanent storage device distinct from the memory. Additionally, an operating system and at least one program code may be stored in the memory (312, 332).

[0082] These software components may be loaded from a computer-readable recording medium separate from memory (312, 332). This separate computer-readable recording medium may include a recording medium that can be directly connected to the user terminal (210) and the information processing system (230), for example, a computer-readable recording medium such as a floppy drive, disk, tape, DVD / CD-ROM drive, or memory card. As another example, the software components may be loaded into memory (312, 332) via a communication module (316, 336) rather than a computer-readable recording medium. For example, at least one program may be loaded into memory (312, 332) based on a computer program installed by files provided through a network (220) by developers or a file distribution system that distributes installation files for the application.

[0083] The processor (314, 334) may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. Instructions may be provided to the processor (314, 334) by memory (312, 332) or a communication module (316, 336). For example, the processor (314, 334) may be configured to execute instructions received according to program code stored in a recording device such as memory (312, 332). The processor (314, 334) may be configured to execute a program for providing a service of assigning orders.

[0084] The communication module (316, 336) may provide a configuration or function for the user terminal (210) and the information processing system (230) to communicate with each other via the network (220), and may provide a configuration or function for the user terminal (210) and / or the information processing system (230) to communicate with another user terminal or another system (e.g., a separate cloud system). For example, a request or data (e.g., information about an order) generated by the processor (314) of the user terminal (210) according to program code stored in a recording device such as memory (312) may be transmitted to the information processing system (230) via the network (220) under the control of the communication module (316). Conversely, a control signal or command provided under the control of the processor (334) of the information processing system (230) can be received by the user terminal (210) through the communication module (336) and the network (220) via the communication module (316) of the user terminal (210).

[0085] The input / output interface (318) may be a means for interfacing with an input / output device (320). As an example, the input device may include a device such as a camera including an audio sensor and / or an image sensor, a keyboard, a microphone, or a mouse, and the output device may include a device such as a display, a speaker, or a haptic feedback device. As another example, the input / output interface (318) may be a means for interfacing with a device in which the configuration or function for performing input and output is integrated into one, such as a touchscreen. For example, when the processor (314) of the user terminal (210) processes instructions of a computer program loaded in memory (312), a service screen configured using information and / or data provided by an information processing system (230) or another user terminal may be displayed on a display through the input / output interface (318). In FIG. 3, the input / output device (320) is depicted as not being included in the user terminal (210), but is not limited thereto and may be configured as a single device with the user terminal (210). Additionally, the input / output interface (338) of the information processing system (230) may be a means for interfacing with a device (not shown) for input or output that is connected to the information processing system (230) or that the information processing system (230) may include. In FIG. 3, the input / output interface (318, 338) is shown as an element configured separately from the processor (314, 334), but is not limited thereto, and the input / output interface (318, 338) may be configured to be included in the processor (314, 334).

[0086] The user terminal (210) and the information processing system (230) may include more components than those of FIG. 3. In one embodiment, the user terminal (210) may be implemented to include at least some of the input / output devices (320) described above. Additionally, the user terminal (210) may include other components such as a transceiver, a GPS (Global Positioning System) module, a camera, various sensors, a database, etc. For example, if the user terminal (210) is a smartphone, it may include components that are generally included in a smartphone, and may be implemented to include various components such as an accelerometer, a gyroscope, a microphone module, a camera module, various physical buttons, buttons using a touch panel, input / output ports, and a vibrator for vibration.

[0087] While a program or application is running, the processor (314) can receive text, images, video, voice and / or actions, etc. that are input or selected through an input device such as a touch screen, keyboard, audio sensor and / or image sensor, camera, microphone, etc. connected to an input / output interface (318), and can store the received text, images, video, voice and / or actions, etc. in memory (312) or provide them to an information processing system (230) through a communication module (316) and a network (220).

[0088] The processor (314) of the user terminal (210) may be configured to manage, process, and / or store information and / or data received from an input / output device (320), another user terminal, an information processing system (230), and / or a plurality of external systems. The information and / or data processed by the processor (314) may be provided to the information processing system (230) through a communication module (316) and a network (220). The processor (314) of the user terminal (210) may transmit information and / or data to the input / output device (320) through an input / output interface (318) to output it. For example, the processor (314) may output or display the received information and / or data on a screen associated with the user terminal (210).

[0089] The processor (334) of the information processing system (230) may be configured to manage, process, and / or store information and / or data received from a plurality of user terminals (210) and / or a plurality of external systems. The information and / or data processed by the processor (334) may be provided to the user terminals (210) through a communication module (336) and a network (220).

[0090] FIG. 4 is a flowchart (400) illustrating an example of a step for generating information regarding a predicted time and information regarding a threshold time according to an embodiment of the present disclosure. In one embodiment, a processor (e.g., a processor (314) of a user terminal (210) of FIG. 3 and / or a processor (334) of an information processing system (230)) may, after step S130 of FIG. 1, generate information regarding a predicted time for a delivery person to perform a delivery order and information regarding a threshold time used for comparison between a reference time and a predicted time, based on information regarding a delivery order and information regarding work conditions. After generating information regarding a predicted time and information regarding a threshold time, step S150 of FIG. 1 may be performed. FIG. 4 describes the process of calculating information regarding a predicted time and information regarding a threshold time.

[0091] In one embodiment, the processor may generate information about a sub-delivery type of a delivery order based on information about a delivery order and information about business conditions (S410). For example, the processor may generate information about a sub-delivery type corresponding to a delivery type based on information about business conditions. For example, the processor may generate information about at least one sub-delivery type for each delivery type.

[0092] In one embodiment, the processor may generate information about an expected route based on information about a delivery order and information about a sub-delivery type (S420). The expected route may be configured such that a pickup location and a drop-off location corresponding to at least one order are connected to each other. The processor may classify cases according to the delivery type and the sub-delivery type, and calculate an expected route for each case. Examples of expected routes calculated for each case will be described in detail with reference to FIGS. 6 and FIGS. 8.

[0093] In one embodiment, the processor may generate information about a residual path for each of at least one order as at least a part of the expected path, based on information about the expected path (S430). A delivery order may be associated with at least one order. The processor may identify a path from the delivery person's current location to a drop-off location as at least a part of the expected path. The processor may define at least a part of the identified expected path as a residual path for each order. A method for generating information about the residual path is described in detail with reference to FIG. 5.

[0094] In one embodiment, the processor may generate information regarding the predicted time for each of at least one order based on information regarding the remaining path (S440). The processor may generate information regarding the predicted time as the time required along the remaining path using the delivery person's means of transportation. For example, the processor may identify at least one of the pickup location or drop-off location of the remaining path on a map. The processor may calculate the predicted time as the time expected to be required for the delivery person to deliver food and / or goods according to the delivery order to the customer by passing through at least one of the identified pickup location or drop-off location using the delivery person's means of transportation.

[0095] In one embodiment, the processor may generate information regarding a threshold time for each of at least one order based on information regarding a delivery order, information regarding a remaining path, and information regarding business conditions (S450). For example, the processor may distinguish at least one situation by distinguishing at least one of the type of delivery order, the number of remaining paths, or the type of means of transportation. A threshold time may be predetermined to correspond to each of at least one situation. Based on information regarding a delivery order, information regarding a remaining path, and information regarding business conditions, the processor may identify a target situation corresponding to at least one distinguished situation. The processor may select a threshold time corresponding to the identified target situation and use the threshold time in a subsequent process.

[0096] In one embodiment, step S450 may be performed after step S440. Alternatively, step S440 may be performed after step S450. Or, steps S440 and S450 may be performed in parallel. In this case, steps S440 and S450 may be performed substantially simultaneously.

[0097] FIG. 5 is a diagram illustrating a method for generating information about a remaining path according to an embodiment of the present disclosure. In FIG. 5, 'E' may represent the current location of a delivery person. 'P1' may represent a pickup location for a first order. 'P2' may represent a pickup location for a second order. 'P3' may represent a pickup location for a third order. 'D1' may represent a drop-off location for a first order. 'D2' may represent a drop-off location for a second order. 'D3' may represent a drop-off location for a third order. In the following, Pn may represent a pickup location for the nth order, and Dn may represent a drop-off location for a third order (n is 0 or a natural number).

[0098] In one embodiment, an expected path (510) may be calculated. Additionally, based on the expected path (510), a first remaining path (520) for a first order, a second remaining path (530) for a second order, and a third remaining path (540) for a third order may be calculated. For example, the first remaining path (520) may correspond to the path from E to D1 among the expected paths (510). The second remaining path (530) may correspond to the path from E to D2 among the expected paths (510). The third remaining path (540) may correspond to the path from E to D3 among the expected paths (510).

[0099] In one embodiment, information regarding the remaining paths may include the number of remaining paths (522, 532, 542). A path moving from one location (e.g., delivery person's current location, pickup location, drop-off location) to another location may be counted as 1 as the number of paths. For example, the number of the first remaining paths (522) may be calculated as 4. The number of the second remaining paths (532) may be calculated as 5. The number of the third remaining paths (542) may be calculated as 5.

[0100] FIG. 6 is a diagram illustrating an example of at least one case according to one embodiment of the present disclosure. At least one case corresponding to at least one of a delivery type (610) or a sub-delivery type (620) may be distinguished. An estimated path (630) may be calculated for each case. Then, based on the estimated path (630), the number of remaining paths (640) for each order may be calculated.

[0101] In one embodiment, the first delivery type may correspond to one order. The 1_1 sub-delivery type and the 1_2 sub-delivery type may be associated with the first delivery type. Referring to FIG. 6, the 1_1 sub-delivery type may correspond to the case where the delivery person is not currently making a delivery. The expected route (630) corresponding to the 1_1 sub-delivery type may be calculated as 'E-P1-D1'. The number of remaining routes (640) for the first order may be 2.

[0102] In one embodiment, information regarding the delivery worker's work conditions may include information associated with the delivery worker's pre-assigned delivery orders. For example, the delivery worker may be scheduled to move to a drop-off location associated with a pre-assigned delivery order to perform the pre-assigned delivery order. The drop-off location associated with the pre-assigned delivery order may be denoted as 'D0'.

[0103] In one embodiment, the first_2 delivery type may correspond to a case where a delivery person is currently making a delivery. The expected route (630) corresponding to the first_2 sub-delivery type may be calculated as 'E-D0-P1-D1'. The number of remaining routes (640) for the first order may be 3.

[0104] In one embodiment, the second delivery type may correspond to two orders. The order of the two orders may not be predetermined. The 2_1 sub-delivery type and the 2_2 sub-delivery type may be associated with the second delivery type.

[0105] In one embodiment, the 2_1 sub-delivery type may correspond to a case where the delivery person is not currently making a delivery. The expected route (630) corresponding to the 2_1 sub-delivery type may be calculated as 'E-P1-P2-D1-D2'. The number of remaining routes (640) for the first order may be 3. The number of remaining routes (640) for the second order may be 4.

[0106] In one embodiment, the 2_2 sub-delivery type may correspond to a case where a delivery person is currently making a delivery. The expected route (630) corresponding to the 2_2 sub-delivery type may be calculated as 'E-D0-P1-P2-D1-D2'. The number of remaining routes (640) for the first order may be 4. The number of remaining routes (640) for the second order may be 5.

[0107] In one embodiment, the third delivery type may correspond to three orders. The order of the three orders may not be predetermined. The 3_1 sub-delivery type and the 3_2 sub-delivery type may be associated with the third delivery type.

[0108] In one embodiment, the 3_1 sub-delivery type may correspond to a case where the delivery person is not currently making a delivery. The expected route (630) corresponding to the 3_1 sub-delivery type may be calculated as 'E-P1-P2-P3-D1-D2-D3'. The number of remaining routes (640) for the first order may be 4. The number of remaining routes (640) for the second order may be 5. The number of remaining routes (640) for the third order may be 6.

[0109] In one embodiment, the 3_2 sub-delivery type may correspond to the case where a delivery person is currently making a delivery. The expected route (630) corresponding to the 2_2 sub-delivery type may be calculated as 'E-D0-P1-P2-P3-D1-D2-D3'. The number of remaining routes (640) for the first order may be 5. The number of remaining routes (640) for the second order may be 6. The number of remaining routes (640) for the third order may be 7.

[0110] FIG. 7 is a diagram illustrating an example of at least one situation according to one embodiment of the present disclosure. At least one situation corresponding to at least one of a delivery type (610), a number of remaining paths (650), or a means of transport (660) may be distinguished in advance. A threshold time (670) may be determined in advance for each situation.

[0111] Information regarding at least one of the delivery type (610), the number of remaining paths (650), or the means of transport (660) is generated, and a target situation may be determined based on said information. A threshold time (670) corresponding to the target situation is selected, and said threshold time (670) may be used to compare a reference time and a predicted time.

[0112] Referring to FIG. 7, if no numerical value is written in the threshold time (670), the threshold time (670) may be 0. The unit of the threshold time (670) may correspond to the unit of the reference time or the predicted time. For example, the unit of the threshold time (670) may be 'minutes', which is the unit of the reference time or the predicted time, but is not limited thereto and may refer to any predetermined unit of time.

[0113] In one embodiment, the target situation may correspond to a delivery type (610) being a first delivery type and a number of remaining paths (650) being 4 or more. In this case, the threshold time (670) may be determined to be 0. Additionally, the target situation may correspond to a delivery type (610) being a first delivery type and a number of remaining paths (650) being less than 4. In this case, the threshold time (670) may be determined to be 0.

[0114] In one embodiment, the target situation may correspond to a delivery type (610) being a second delivery type and a number of remaining paths (650) being 4 or more. In this case, the threshold time (670) may differ depending on the means of transportation (660). For example, if the means of transportation (660) in that situation is a vehicle, the threshold time (670) may be determined to be -5. If the means of transportation (660) in that situation is a motorcycle, the threshold time (670) may be determined to be 2. If the means of transportation (660) in that situation is a bicycle, the threshold time (670) may be determined to be 5.

[0115] In one embodiment, the target situation may correspond to a delivery type (610) being a second delivery type and a number of remaining paths (650) being less than 4. In this case, the threshold time (670) may be determined to be 0.

[0116] In one embodiment, the target situation may correspond to a delivery type (610) being a third delivery type and a number of remaining paths (650) being 5 or more. In this case, the threshold time (670) may be determined to be -5.

[0117] In one embodiment, the target situation may correspond to a delivery type (610) being a third delivery type and a number of remaining paths (650) being less than 5. In this case, the threshold time (670) may vary depending on the means of transportation (660). For example, if the means of transportation (660) in that situation is a vehicle, the threshold time (670) may be determined to be -5. If the means of transportation (660) in that situation is a motorcycle or a bicycle, the threshold time (670) may be determined to be 0.

[0118] In one embodiment, at least one situation may be classified in various ways according to the delivery type (610), the number of remaining paths (650), the means of transportation (660), etc., and various threshold times (670) may be determined accordingly. The plurality of situations disclosed in FIG. 7 are set as examples, and different threshold times may be set for the same situation due to various factors such as the order region, the order time, etc.

[0119] FIG. 8 is a drawing illustrating an example of at least one case according to one embodiment of the present disclosure. At least one case corresponding to at least one of a delivery type (810) or a sub-delivery type (820) may be distinguished. For each case, an expected path (830) may be calculated. Then, based on the expected path (830), the number of remaining paths (840) for each order may be calculated.

[0120] In one embodiment, the fourth delivery type may correspond to two orders. For example, a delivery order may be associated with a first order and a second order. The delivery order may be determined such that the second order is executed after the first order is executed. For example, a delivery person assigned to the delivery order may visit the drop-off location of the second order after passing through the drop-off location of the first order. As another example, the fourth delivery type may include a case where a delivery person who has been previously assigned the first order is additionally assigned the second order.

[0121] In one embodiment, 4_1 sub-delivery types to 4_3 sub-delivery types may be associated with 4 delivery types. 4_1 sub-delivery type may correspond to the case before the delivery person visits the pickup location for the 1st order. The expected route (830) corresponding to 4_1 sub-delivery type may be calculated as 'E-P1-P2-D1-D2'. The number of remaining routes (840) for the 1st order may be 2.

[0122] In one embodiment, the 4_2 sub-delivery type may correspond to the case where the delivery person has visited the pickup location for the 1st order. The expected route (830) corresponding to the 4_2 sub-delivery type may be calculated as 'E-P2-D1-D2'. The number of remaining routes (840) for the 1st order may be 3.

[0123] In one embodiment, a delivery person may be performing work for a zero order assigned before a first order. The zero order may have a predetermined relationship with the first order. For example, it may be predetermined that the first order is performed after the zero order is performed.

[0124] In one embodiment, the 4_3 sub-delivery type may correspond to a case where a delivery person is performing a 0th order different from the 1st order and the 2nd order. The 4_3 sub-delivery type may include a 1st case and a 2nd case. The 1st case of the 4_3 sub-delivery type may correspond to a case where a delivery person is currently moving to a drop-off location for the 0th order. The expected route (830) corresponding to the 1st case of the 4_3 sub-delivery type may be calculated as 'E-D0-P1-P2-D1-D2'. The number of remaining routes (840) for the 1st order may be 3. The number of remaining routes (840) for the 2nd order may be 4.

[0125] In one embodiment, the second case of the 4_3 sub-delivery may correspond to a case where the delivery person is currently moving to the pickup location for the first order. The delivery person may be predetermined to perform the first order after performing the 0 order. The expected route (830) corresponding to the second case of the 4_3 sub-delivery may be calculated as 'E-P1-D0-D1-P2-D2'. The number of remaining routes (840) for the first order may be 4. The number of remaining routes (840) for the second order may be 5.

[0126] In one embodiment, the fifth delivery type may correspond to three orders. For example, a delivery order may be associated with a first order, a second order, and a third order. The delivery order may be determined such that the third order is executed after the first and second orders have been executed. For example, a delivery person assigned to the delivery order may visit the drop-off location of the third order after passing through the drop-off location of the first order and the drop-off location of the second order. As another example, the fifth delivery type may include a case where a delivery person who has been pre-assigned the first and second orders is additionally assigned the third order. As yet another example, the fifth delivery type may include a case where a delivery person who has been pre-assigned the first order is additionally assigned the second and third orders.

[0127] In one embodiment, 5_1 sub-delivery types to 5_3 sub-delivery types may be associated with 5 delivery types. 5_1 sub-delivery type may include a first case and a second case. The first case of 5_1 sub-delivery type may correspond to a case before the delivery person visits the pickup location for the first order. The expected route (830) corresponding to the first case of 5_1 sub-delivery type may be calculated as 'E-P1-P2-P3-D1-D2-D3'. The number of remaining routes (840) for the first order may be 4. The number of remaining routes (840) for the second order may be 5. The number of remaining routes (840) for the third order may be 6.

[0128] In one embodiment, the second case of the 5_1 sub-delivery type may correspond to a case before the delivery person visits the pickup location for the second order. The expected route (830) corresponding to the second case of the 5_1 sub-delivery type may be calculated as 'E-P2-P3-D1-D2-D3'. The number of remaining routes (840) for the first order may be 3. The number of remaining routes (840) for the second order may be 4. The number of remaining routes (840) for the third order may be 5.

[0129] In one embodiment, the 5_2 sub-delivery type may correspond to the case where the delivery person has visited the pickup location for the second order. The expected route (830) corresponding to the 5_2 sub-delivery type may be calculated as 'E-P3-D1-D2-D3'. The number of remaining routes (840) for the first order may be 2. The number of remaining routes (840) for the second order may be 3. The number of remaining routes (840) for the third order may be 4.

[0130] In one embodiment, the 5_3 sub-delivery type may correspond to a case where a delivery person is performing a 0th order different from the 1st to 3rd orders. The 5_3 sub-delivery type may include a 1st case and a 2nd case. The 1st case of the 5_3 sub-delivery type may correspond to a case where a delivery person is currently moving to a pickup location for the 1st order. The expected route (830) corresponding to the 1st case of the 5_3 sub-delivery type may be calculated as 'E-P1-D0-D1-P2-P3-D2-D3'. The number of remaining routes (840) for the 0th order may be 2. The number of remaining routes (840) for the 1st order may be 3. The number of remaining routes (840) for the 2nd order may be 6. The number of remaining routes (840) for the 3rd order may be 7.

[0131] In one embodiment, the second case of the 5_3 sub-delivery type may correspond to the case where a delivery person is currently moving to a drop-off location for the 0th order. The expected route (830) corresponding to the second case of the 5_3 sub-delivery type may be calculated as 'E-D0-P1-P2-P3-D1-D2-D3'. The number of remaining routes (840) for the 1st order may be 5. The number of remaining routes (840) for the 2nd order may be 6. The number of remaining routes (840) for the 3rd order may be 7.

[0132] FIG. 9 is a diagram illustrating an example of at least one situation according to one embodiment of the present disclosure. At least one situation corresponding to at least one of a delivery type (810), a number of remaining paths (850), or a means of transport (860) may be distinguished in advance. A threshold time (870) may be determined in advance for each situation.

[0133] Information regarding at least one of the delivery type (810), the number of remaining paths (850), or the means of transportation (860) is generated, and a target situation may be determined based on said information. A threshold time (870) corresponding to the target situation is selected, and said threshold time (870) may be used for comparison between a reference time and a predicted time.

[0134] Referring to FIG. 9, the unit of the critical time (870) may correspond to the unit of the reference time or the predicted time. For example, the unit of the critical time (870) may be 'minutes', which is the unit of the reference time or the predicted time, but is not limited thereto.

[0135] In one embodiment, the target situation is that the delivery type (810) is the fourth delivery type, the number of remaining paths (850) is 4 or more, and the threshold time (870) may vary depending on the means of transportation (860). For example, in the situation, if the means of transportation (860) is a vehicle, the threshold time (870) may be determined to be -5. In the situation, if the means of transportation (860) is a motorcycle or a bicycle, the threshold time (870) may be determined to be 5.

[0136] In one embodiment, the target situation may correspond to a delivery type (810) being a fourth delivery type and a number of remaining paths (850) being less than 4. In this case, the threshold time (870) may be determined to be 5.

[0137] In one embodiment, the target situation may correspond to a delivery type (810) being the fifth delivery type and a number of remaining paths (850) being 5 or more. In this case, the threshold time (870) may differ depending on the means of transportation (860). For example, if the means of transportation (860) in that situation is a vehicle, the threshold time (870) may be determined to be -10. If the means of transportation (860) in that situation is a motorcycle or a bicycle, the threshold time (870) may be determined to be -5.

[0138] In one embodiment, the target situation may correspond to a delivery type (810) being the fifth delivery type and a number of remaining paths (850) being less than 5. The threshold time (870) may vary depending on the means of transportation (860). For example, if the means of transportation (860) in the situation is a vehicle, the threshold time (870) may be determined to be -5. If the means of transportation (860) in the situation is a motorcycle or a bicycle, the threshold time (870) may be determined to be 0.

[0139] In one embodiment, if the target situation does not correspond to at least one predetermined situation, the threshold time may be determined as a predetermined time. For example, the threshold time may be determined as 5 minutes.

[0140] In one embodiment, the processor may include information regarding a delivery order and information regarding a work condition, and information regarding a target condition associated with the information regarding the work condition. The processor may determine whether the information regarding the delivery order and the information regarding the work condition satisfy the target condition. Then, based on the determination result, the processor may determine a threshold time (870) as a predetermined time. For example, the target condition may include a condition that the means of transportation is walking. 5 minutes may be determined as a predetermined time corresponding to the condition that the means of transportation is walking. The processor may identify information among the information regarding the delivery order and the information regarding the work condition that the delivery person's means of transportation (860) is walking and determine that the target condition is satisfied. Based on the determination result, the processor may determine the threshold time (870) as 5 minutes.

[0141] In one embodiment, the processor may select a threshold time (870) determined by determining whether a target condition is satisfied, regardless of whether the target situation corresponds to at least one distinguished situation. For example, the target condition may include a condition where the means of transportation (860) is a vehicle. -10 minutes may be determined as a predetermined time corresponding to the condition where the means of transportation (860) is a vehicle. The processor may identify information regarding the delivery order and the information regarding the work condition where the delivery person's means of transportation (860) is a vehicle, and determine that the target condition is satisfied. Based on the determination result, the processor may determine that the threshold time (870) is -10 minutes. The target situation may correspond to a case where the delivery type (810) is the fourth delivery type and the number of remaining paths (850) is 4 or more. Since the means of transportation (860) is a vehicle, the threshold time (870) may correspond to -5. The processor may not determine the threshold time (870) to be -5 minutes. Instead, the processor may determine the threshold time (870) for the target condition first and determine the threshold time (870) to be -10 minutes.

[0142] In one embodiment, at least one situation may be classified in various ways according to the delivery type (810), the number of remaining paths (850), the means of transportation (860), etc., and various threshold times (870) may be determined accordingly. The plurality of situations disclosed in FIG. 9 are set as examples, and different threshold times may be set for the same situation due to various factors such as the order region, the order time, etc.

[0143] FIG. 10 is a flowchart (1000) illustrating an example of a method for assigning a delivery order to a delivery person according to one embodiment of the present disclosure. In one embodiment, after step S140 of FIG. 1, the processor may determine whether to assign a delivery order to a delivery person based on a reference time, a predicted time, and a threshold time. For example, the processor may determine whether to assign a delivery order to a delivery person based on a comparison of the sum of the predicted time and the threshold time and the reference time.

[0144] Specifically, the processor can compare the sum of the predicted time and the threshold time with the reference time (S1010). If the processor determines that the sum of the predicted time and the threshold time is greater than the reference time, it may decide not to assign the delivery order to the delivery person (S1012). Alternatively, if the sum of the predicted time and the threshold time is less than or equal to the reference time, the processor may decide to assign the delivery order to the delivery person (S1020).

[0145] FIG. 11 is a flowchart (1100) illustrating an example of a method for assigning a delivery order to a delivery person according to one embodiment of the present disclosure. In one embodiment, after step S140 of FIG. 1, the processor may determine whether to assign a delivery order to a delivery person based on a reference time, a predicted time, and a threshold time.

[0146] In one embodiment, a delivery order may be associated with a plurality of orders. The plurality of orders may include orders currently being performed by a delivery person, pre-assigned orders, etc. The plurality of orders may further include orders to be assigned using the order assignment method of the present disclosure. Referring to FIG. 5, a delivery order may be associated with orders 0 through 3 in the first case of the 5_3 sub-delivery type. A delivery order may be associated with orders 1 through 3 in the second case of the 5_3 sub-delivery type. A delivery order described below may be associated with orders 1 and 2.

[0147] In one embodiment, the processor may obtain information regarding a first reference time associated with a first order and information regarding a second reference time associated with a second order. Additionally, the processor may obtain information regarding a first prediction time associated with a first order, information regarding a first threshold time, information regarding a second prediction time associated with a second order, and information regarding a second threshold time. The processor may obtain information regarding a first reference time, information regarding a first prediction time, and information regarding a first threshold time for a first order using the method described above. Furthermore, the processor may obtain information regarding a second reference time, information regarding a second prediction time, and information regarding a second threshold time for a second order.

[0148] In one embodiment, the processor may compare the sum of the first prediction time and the first threshold time with the first reference time (S1120). If the processor determines that the sum of the first prediction time and the first threshold time is greater than the first reference time, it may decide not to assign the delivery order to the delivery person (S1122). If the processor determines that the sum of the first prediction time and the first threshold time is less than or equal to the first reference time, it may compare the sum of the second prediction time and the second threshold time with the second reference time (S1130).

[0149] In one embodiment, if the processor determines that the sum of the second prediction time and the second threshold time is greater than the second reference time, it may decide not to assign the delivery order to the delivery person (S1132). If the processor determines that the sum of the second prediction time and the second threshold time is less than or equal to the second reference time, it may decide to assign it to the delivery person (S1140).

[0150] In one embodiment, if the processor determines that a delivery order will not be assigned to a delivery person, the order previously assigned to the delivery person may be retained. For example, a delivery order may be associated with a first order and a second order. The first order may be assigned to the delivery person in advance, and the second order may be an order to be assigned using the order assignment method of the present disclosure. If it is determined that a delivery order will not be assigned to a delivery person, the assignment of the first order to the delivery person may be retained, and the second order may not be assigned to the delivery person.

[0151] The method described above may be provided as a computer program stored on a computer-readable recording medium for execution on a computer. The medium may continuously store a program executable by a computer, or temporarily store it for execution or download. Additionally, the medium may be various recording or storage means in the form of a single or multiple hardware components combined, and may not be limited to a medium directly connected to a computer system but may exist distributed over a network. Examples of media may include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and media configured to store program instructions, including ROM, RAM, and flash memory. Furthermore, other examples of media may include recording or storage media managed by app stores that distribute applications or sites and servers that supply or distribute various other software.

[0152] The methods, operations, or techniques of the present disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or a combination thereof. Those skilled in the art will understand that the various exemplary logical blocks, modules, circuits, and algorithmic steps described in connection with the disclosure herein may be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate such interchangeability between hardware and software, various exemplary components, blocks, modules, circuits, and steps have been generally described above in terms of their functional aspects. Whether such functions are implemented in hardware or in software depends on the design requirements imposed on the specific application and the overall system. Those skilled in the art may implement the functions described in various ways for each specific application, but such implementations should not be construed as departing from the scope of the present disclosure.

[0153] In a hardware implementation, the processing units used to perform the techniques may be implemented in one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described in this disclosure, computers, or a combination thereof.

[0154] Accordingly, the various exemplary logic blocks, modules, and circuits described in connection with the present disclosure may be implemented or performed by any combination of general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or those designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but alternatively, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, for example, a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors coupled with a DSP core, or any other combination of configurations.

[0155] In firmware and / or software implementations, techniques may be implemented as instructions stored on a computer-readable medium such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage devices, etc. The instructions may be executable by one or more processors, and may cause the processor(s) to perform specific aspects of the functions described in this disclosure.

[0156] Where implemented in software, the techniques may be stored on a computer-readable medium as one or more instructions or code, or transmitted through a computer-readable medium. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible by a computer. As a non-limiting example, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium accessible by a computer that can be used to transfer or store desired program code in the form of instructions or data structures. Additionally, any connection is appropriately referred to as a computer-readable medium.

[0157] For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair cable, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, coaxial cable, fiber optic cable, twisted pair cable, digital subscriber line, or wireless technologies such as infrared, radio, and microwave are included within the definition of a medium. As used herein, disk and disc include CD, laser disc, optical disc, DVD (digital versatile disc), floppy disk, and Blu-ray disc, wherein disks usually play data magnetically, whereas discs play data optically using a laser. The above combinations should also be included within the scope of computer-readable media.

[0158] The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other known form of storage medium. An exemplary storage medium may be connected to a processor so that the processor can read information from the storage medium or write information to the storage medium. Alternatively, the storage medium may be integrated into the processor. The processor and the storage medium may exist within an ASIC. The ASIC may exist within a user terminal. Alternatively, the processor and the storage medium may exist as separate components within the user terminal.

[0159] Although the embodiments described above have been described as utilizing aspects of the subject matter disclosed herein in one or more standalone computer systems, the present disclosure is not limited thereto and may be implemented in conjunction with any computing environment, such as a network or a distributed computing environment. Furthermore, aspects of the subject matter in the present disclosure may be implemented in a plurality of processing chips or devices, and storage may be similarly affected across a plurality of devices. Such devices may include PCs, network servers, and portable devices.

[0160] Although the present disclosure has been described in relation to some embodiments, various modifications and changes may be made without departing from the scope of the present disclosure as understood by a person skilled in the art to which the invention of the present disclosure pertains. Furthermore, such modifications and changes should be considered to fall within the scope of the claims appended to this specification.

Claims

1. A step of obtaining information about a delivery order; Step of identifying information regarding the working conditions of the delivery person; A step of obtaining information regarding the standard time provided to the customer who requested the above delivery order; A step of generating, based on information regarding the delivery order and information regarding the work conditions, information regarding the predicted time for the delivery person to perform the delivery order and information regarding the threshold time used for comparison between the reference time and the predicted time; and A step of determining whether to assign the delivery order to the delivery person based on the above reference time, the above prediction time, and the above threshold time. An order assignment method including 2. In Paragraph 1, An order assignment method comprising information regarding the above work conditions, including information associated with at least one of the delivery status of the delivery person or the means of transportation of the delivery person.

3. In Paragraph 1, The step of generating the above is, Based on the information regarding the delivery order and the information regarding the work conditions, the step of generating information regarding the expected route for the delivery person to perform the delivery order An order assignment method including 4. In Paragraph 3, An order assignment method in which information regarding the above delivery order includes information regarding the delivery type of the above delivery order.

5. In Paragraph 4, The step of generating information about the above-mentioned expected path is, A step of generating information on the sub-delivery type of the delivery order based on the information on the delivery type and the information on the business conditions; and Step of generating information about the expected route based further on the information about the sub-delivery type above. An order assignment method including 6. In Paragraph 3, The above delivery order is associated with at least one order, and The step of generating the above is, Based on the information regarding the above-mentioned expected path, the step of generating information regarding the remaining path for each of the at least one order as at least part of the above-mentioned expected path; and A step of generating information on the predicted time for each of the at least one order based on information on the remaining path above. An order assignment method that further includes 7. In Paragraph 6, The step of generating the above is, A step of generating information on the threshold time for each of the at least one order based on information on the above remaining path. An order assignment method that further includes 8. In Paragraph 1, The information regarding the above delivery order includes information regarding the delivery type of the above delivery order, The step of generating the above is, A step of generating information about the threshold time based on information about the delivery type above. An order assignment method including 9. In Paragraph 1, The information regarding the above delivery order includes information regarding the delivery type of the above delivery order, The step of generating the above is, A step of generating information on the sub-delivery type of the delivery order based on the information on the delivery type and the information on the business conditions; and A step of generating information about the threshold time based on information about the sub-delivery type above. An order assignment method including 10. In Paragraph 1, A step of obtaining information about target conditions associated with information about the above delivery order and information about the above business conditions Includes more, The step of generating the above is, A step of determining whether the information regarding the delivery order and the information regarding the business conditions above satisfy the target conditions; and A step of determining the threshold time as a predetermined time based on the above judgment result An order assignment method including 11. In Paragraph 1, The step of determining whether to assign the above delivery order to the above delivery person is, A step of determining whether to assign the delivery order to the delivery person based on a comparison of the sum of the predicted time and the threshold time and the reference time. An order assignment method including 12. In Paragraph 11, The step of determining whether to assign to the delivery person based on a comparison of the sum of the predicted time and the threshold time and the reference time is, A step of deciding not to assign the delivery order to the delivery person if the sum of the predicted time and the threshold time is greater than the reference time; or A step of deciding to assign the delivery order to the delivery person when the sum of the above prediction time and the above threshold time is less than or equal to the above reference time. An order assignment method including 13. In Paragraph 1, The above delivery order is associated with the first order and the second order, and The step of obtaining information regarding the above reference time is, A step of obtaining information regarding a first reference time associated with the first order and information regarding a second reference time associated with the second order. Includes, The step of generating the above is, A step of obtaining information regarding a first prediction time associated with the first order, information regarding a first threshold time, information regarding a second prediction time associated with the second order, and information regarding a second threshold time. An order assignment method including 14. In Paragraph 13, The step of determining whether to assign the above delivery order to the above delivery person is, A step of determining whether to assign the delivery order to the delivery person based on at least one of a comparison between the sum of the first prediction time and the first threshold time and the first reference time, or a comparison between the sum of the second prediction time and the second threshold time and the second reference time. An order assignment method including 15. A computer-readable recording medium recording instructions for executing a method according to any one of paragraphs 1 through 14 on a computer.

16. As an information processing system, Memory; and At least one processor connected to the memory and configured to execute at least one computer-readable program contained in the memory. Includes, The above at least one program is, Obtain information about delivery orders, Identify information regarding the working conditions of delivery personnel, and Obtain information regarding the standard time provided to the customer who requested the above delivery order, and Based on the information regarding the delivery order and the information regarding the work conditions, the delivery person generates information regarding the predicted time for performing the delivery order and information regarding the threshold time used for comparison between the reference time and the predicted time, and An information processing system comprising instructions for determining whether to assign the delivery order to the delivery person based on the above reference time, the above prediction time, and the above threshold time.

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