Method for generating dispatch plan

Abstract

The present invention relates to a method for generating a dispatch plan performed by a server. The method comprises: a first step for acquiring first area information including area designation for each of a plurality of dispatch vehicles; a second step for generating second area information related to the plurality of designated areas; a third step for registering the first area information and the second area information with respect to the dispatch vehicles; and a fourth step for generating a dispatch plan by using the registered first area information and second area information.

Description

How to create a dispatch plan

[0001] The present disclosure relates to a method for a server to generate a dispatch plan for a delivery order. Specifically, the method relates to a method for generating a plan that utilizes order information and vehicle information to ensure the most efficient delivery when the server generates a dispatch plan for multiple delivery orders.

[0002] Typically, a consumer purchases a product by checking it out in person or online and then paying for it, thereby acquiring ownership. This process can involve viewing the product in person and then receiving it on the spot. Others involve checking it out online and then paying for it and receiving it later. One method of receiving it later is by using a courier service.

[0003] Using a courier service means delivering mail, luggage, products, etc. directly to the requested location. The products are collected at a collection point for delivery and each is delivered to its destination.

[0004] At this time, the destinations of each product vary, and delivery requirements also vary. Accordingly, delivery must be made using an appropriate vehicle and adhering to the target delivery time.

[0005] Additionally, the recent pandemic has led to an increase in consumers using home delivery services to receive products at home. Consequently, ensuring that delivery is made in the shortest possible time and via the most optimal route is becoming a key priority for the courier logistics system.

[0006] Accordingly, research is ongoing into ways to dispatch vehicles in a way that minimizes the manpower of the dispatching company while ensuring smooth delivery of goods and punctual delivery.

[0007] The purpose of the present invention is to provide a method that enables a delivery company to separate the areas in which vehicles can operate and areas in which vehicles cannot operate by using the area information and operating time information of the dispatched vehicles when establishing a dispatch plan.

[0008] An embodiment of the present disclosure for solving the above-described problem may include a method for generating a dispatch plan performed by a server, the method comprising: obtaining first region information including a plurality of region designations for a dispatched vehicle; generating second region information associated with the plurality of designated regions; registering the first region information and the second region information for the dispatched vehicle; and generating a dispatch plan using the registered first region information and the second region information.

[0009] The above first region information is a region in which the dispatch vehicle can deliver, and the above second region information may be a region that overlaps with the above first region information.

[0010] The step of generating the above dispatch plan can generate a first zone dispatch plan using the minimum movement path within the first zone information of each dispatch vehicle.

[0011] The step of generating the above dispatch plan may include generating a second zone dispatch plan in which delivery to the second zone information is excluded from the first zone dispatch plan for vehicles whose operating time is greater than or equal to a first threshold value among the first zone dispatch plans.

[0012] Among the above-mentioned secondary zone dispatch plans, the first zone that includes vehicles with a running time exceeding the first threshold may allow dispatch of external vehicles.

[0013] The step of generating the above dispatch plan may include generating a third zone dispatch plan by additionally dispatching order information of the second zone for vehicles whose operating time is less than the first threshold among the first zone dispatch plans.

[0014] The first region information and the second region information include a preferred region or an avoided region, and the preferred region and the avoided region include cost information, and the third step can adjust the cost based on the cost information.

[0015] The third step above can assign weights to costs within the avoidance zone.

[0016] The third step may, if the aversion zone and the preferred zone overlap, deduct a certain amount of cost for the overlapping zone.

[0017] The fourth step may generate a dispatch plan that minimizes the cost, and if the costs are the same, may generate the dispatch plan by selecting a priority for the optimal route.

[0018] According to one embodiment of the present disclosure, there is an effect of enabling customized delivery for each vehicle by forming a delivery route that meets the conditions of each vehicle during the process of storing products in a warehouse according to product orders and delivering them to consumers.

[0019] Additionally, it has the effect of preventing the phenomenon of work being concentrated on each vehicle due to excessive or insufficient work being divided during delivery.

[0020] FIG. 1 is a schematic diagram illustrating a scheme in which automatic dispatching is performed by a server according to an embodiment of the present disclosure.

[0021] FIG. 2 is a diagram schematically illustrating each step of a method for optimizing the operation time of a dispatched vehicle according to the first embodiment of the present disclosure.

[0022] FIG. 3 is a diagram schematically illustrating a process of a method for optimizing the operation time of a dispatched vehicle according to a first embodiment of the present disclosure.

[0023] FIG. 4 is a diagram schematically illustrating a process of a dispatch plan generation method according to a second embodiment of the present disclosure.

[0024] FIG. 5 is a schematic diagram illustrating an example of a dispatch plan generation method according to a second embodiment of the present disclosure.

[0025] FIG. 6 is a schematic diagram illustrating an example of a dispatch plan generation method according to a third embodiment of the present disclosure.

[0026] FIG. 7 is a diagram schematically illustrating an example of a process of a method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure.

[0027] FIG. 8 is a schematic diagram illustrating another example of a method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure.

[0028] FIG. 9 is a diagram illustrating a server according to one embodiment of the present disclosure.

[0029] FIG. 10 is a general schematic diagram of an exemplary server environment in which embodiments of the present disclosure may be implemented.

[0030] Various embodiments are now described with reference to the drawings. In this specification, various descriptions are provided to facilitate understanding of the present disclosure. However, it will be apparent that these embodiments may be practiced without these specific details.

[0031] As used herein, the terms "component," "module," "system," and the like refer to computer-related entities, hardware, firmware, software, a combination of software and hardware, or an execution of software. For example, a component may be, but is not limited to, a procedure running on a processor, a processor, an object, a thread of execution, a program, and / or a computer. For example, an application running on a server and the server itself may both be components. One or more components may reside within a processor and / or a thread of execution. A component may be localized within a single computer. A component may be distributed between two or more computers. Furthermore, these components may execute from various computer-readable media having various data structures stored therein. Components may communicate via local and / or remote processes, for example, by signals comprising one or more data packets (e.g., data from one component interacting with another component in a local system, a distributed system, and / or data transmitted to another system via a network such as the Internet via signals).

[0032] Furthermore, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from context, "X employs A or B" is intended to mean either of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, "X employs A or B" can apply to any of these cases. Furthermore, the term "and / or" as used herein should be understood to refer to and include all possible combinations of one or more of the associated items listed.

[0033] Additionally, the terms "comprises" and / or "comprising" should be understood to imply the presence of the features and / or components in question. However, it should be understood that the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other features, components, and / or groups thereof. Furthermore, unless otherwise specified or clear from the context to refer to the singular form, the singular in the specification and claims should generally be construed to mean "one or more."

[0034] And, the term "at least one of A or B" should be interpreted to mean "if it includes only A", "if it includes only B", or "if it is combined in the composition of A and B".

[0035] Those skilled in the art should further appreciate that the various illustrative logical blocks, configurations, modules, circuits, means, logics, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application. However, such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0036] The description of the disclosed embodiments is provided to enable those skilled in the art to make or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Therefore, the present invention is not limited to the embodiments disclosed herein. The present invention is to be construed in the widest scope consistent with the principles and novel features disclosed herein.

[0037]

[0038] Hereinafter, the present disclosure will be described with reference to the drawings.

[0039]

[0040] FIG. 1 is a schematic diagram showing a scheme in which automatic dispatching is performed by a server according to an embodiment of the present disclosure, FIG. 2 is a schematic diagram showing each step of a method for optimizing the operation time of a dispatched vehicle according to a first embodiment of the present disclosure, FIG. 3 is a schematic diagram showing a process of a method for optimizing the operation time of a dispatched vehicle according to a first embodiment of the present disclosure, FIG. 4 is a schematic diagram showing a process of a method for generating a dispatch plan according to a second embodiment of the present disclosure, FIG. 5 is a schematic diagram showing an example of a method for generating a dispatch plan according to a second embodiment of the present disclosure, FIG. 6 is a schematic diagram showing an example of a method for generating a dispatch plan according to a third embodiment of the present disclosure, FIG. 7 is a schematic diagram showing an example of a process of a method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure, FIG. 8 is a schematic diagram showing another example of a method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure, and FIG. 9 is a schematic diagram showing a method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure. A drawing for explaining a server according to an embodiment, and FIG. 10 is a general schematic diagram of an exemplary server environment in which embodiments of the present disclosure can be implemented.

[0041]

[0042] Referring to FIG. 1, the present disclosure relates to a method for optimizing dispatch of delivery vehicles performed by a server (100). The server (100) may obtain order information from a consumer (terminal), obtain information on each delivery vehicle, automatically calculate an efficient dispatch of each vehicle for delivery, and recommend dispatch result information to the delivery vehicles. Hereinafter, this will be described in detail through various embodiments.

[0043]

[0044] According to a first embodiment of the present disclosure with reference to FIG. 2, a method for optimizing the operating time of a dispatched vehicle performed by a server (100) may be such that, when an order for a product purchase is received, the server (100) automatically calculates and recommends a dispatch for delivery of each product through delivery location information for each order information. Specifically, the method may include a first step (S210) of setting the maximum operating time of a dispatched vehicle; a second step (S220) of generating a dispatch plan considering the maximum operating time (wherein the dispatch plan includes an operating time according to a driving route); a third step (S230) of verifying the dispatch plan using order information; and a fourth step (S240) of changing the maximum operating time and repeatedly performing the second step (S220) and the third step (S230) for the changed maximum operating time, thereby searching for a value at which the maximum operating time is minimized.

[0045] Here, the maximum operating time of a dispatched vehicle may be the sum of the maximum operating times of multiple dispatched vehicles, or the maximum operating times of each dispatched vehicle. It may also be the maximum operating time for each vehicle.

[0046] Additionally, order information may be information about a consumer's purchase of a product. Specifically, it may include information about the product being shipped, the product's collection point (origin), and the product's delivery location (destination). This information may be obtained through the consumer's terminal. Furthermore, the dispatch plan may be a plan for delivering the product to the delivery location based on order information.

[0047] Additionally, the first step (S210) may be for the server (100) to designate a maximum operating time for each dispatched vehicle. Here, the maximum operating time may mean that a maximum operating time is designated for each vehicle, and may be the sum of the maximum operating times of each vehicle.

[0048] Additionally, the second step (S220) may be to generate a route that can be operated within the maximum operating time for each vehicle. In other words, it may be to generate a dispatch plan that utilizes the shortest distance route that can be operated within the maximum operating time.

[0049] Additionally, the third step (S230) may verify the dispatch plan generated in the second step (S220). That is, it may verify whether the delivery according to the dispatch plan is delivered via the shortest distance and time.

[0050] Additionally, Step 4 may explore ways to maximize efficiency by changing the maximum operating time for the dispatch plan verified in Step 3 (S230). Specifically, by changing the maximum operating time, dispatch plans may be implemented in the shortest possible time using the shortest distance.

[0051]

[0052] According to the first embodiment of the present disclosure, in the first step (S210), the maximum operation time may be arbitrarily set by the server (100) for each dispatched vehicle.

[0053] That is, the server (100) may arbitrarily designate a maximum operating time and calculate a travel route and travel time based on the designated maximum operating time. The arbitrarily designated maximum operating time may be 12 hours or less per day. This may be done by designating the maximum operating time within the environment in which personnel can work, as personnel are required to operate a single vehicle.

[0054]

[0055] According to the first embodiment of the present disclosure, the second step (S220) may be to generate a dispatch plan having a maximum operating route that each of the dispatched vehicles can travel during the maximum operating time.

[0056] Here, the movable route is formed by roads that can be navigated and roads that cannot be navigated, depending on the characteristics of each vehicle. The route can be a route that travels along these roads. This route can be the shortest route to the next delivery location. Furthermore, the dispatch plan can be a plan that calculates the route for each vehicle based on its maximum travel time and compiles all calculated routes. The route can be a route for delivery vehicles that uses each delivery location as a base.

[0057]

[0058] According to the first embodiment of the present disclosure, the order information of the third step (S230) is delivery information including a departure point and a destination, and if the dispatch plan enables delivery of the entire order information, it may be classified as a possible dispatch plan.

[0059] Here, a feasible dispatch plan calculates a route within the maximum operating time for each vehicle, and all deliveries within the order information are made for the entire calculated route. In other words, if a dispatch plan is classified as feasible, it means that all orders required by the order information are deliverable.

[0060] However, if the dispatch schedule is finalized, the entire maximum operating time may be used, or the dispatch schedule may be finalized within the maximum operating time, meaning that deliveries will be made within the maximum operating time.

[0061]

[0062] According to the first embodiment of the present disclosure, the third step (S230) may classify the dispatch plan as an impossible dispatch plan if delivery of the entire order information is impossible.

[0063] Here, an impossible dispatch plan refers to a situation where all order information cannot be delivered within the maximum operating time for each vehicle. This means that while the route is designed to utilize the maximum operating time for each vehicle, there are still deliveries that remain. In cases where a dispatch plan is classified as impossible, additional dispatching is required to accommodate the remaining deliveries, as explained below.

[0064]

[0065] Referring to FIG. 3, according to the first embodiment of the present disclosure, in the fourth step (S240), if the dispatch plan is classified as the possible dispatch plan, the second step (S220) and the third step (S230) are repeated by reducing the maximum operating time, but if the changed maximum operating time is classified as an impossible dispatch plan, the dispatch plan for the maximum operating time before the change can be determined as the first modified dispatch plan.

[0066] Here, the first modified dispatch plan may be a dispatch plan that has a minimum maximum travel time by going through steps 1 (S210) to 4. In other words, it may be a dispatch plan in which dispatch is recommended after dispatching for each delivery is completed.

[0067] Additionally, a possible dispatch plan is one that allows for the delivery of all order information among dispatch plans based on any maximum operating time specified by the server (100). However, this means that there are fewer delivery orders compared to the number of vehicles available. In other words, if there are too few deliveries, some vehicles may not perform any transport. This can lead to waste of manpower and vehicles.

[0068] Accordingly, the server (100) adjusts the maximum operating time and performs additional steps. Specifically, since delivery is completed within the maximum operating time, the maximum operating time may be reduced and the dispatch plan recalculated. In other words, the goal may be to find the maximum operating time that maximizes efficiency while minimizing vehicle and operating time usage.

[0069] As described above, if the maximum operating time is reduced, the second step (S220) and third step (S230) are repeated to classify the dispatch plan based on the changed maximum operating time as possible or impossible. Here, if the dispatch plan is classified as possible again, the maximum operating time is reduced again, and the second step (S220) and third step (S230) are repeated using the reduced maximum operating time. If the resulting dispatch plan is classified as impossible, the dispatch plan is unusable and therefore unusable, and the possible dispatch plan using the maximum operating time before the previous change may be classified as the first revised dispatch plan.

[0070] For example, when performing dispatch for 4 vehicles, a dispatch plan is established by specifying an arbitrary maximum operating time as 8,8,8,8, and if the result is classified as a possible dispatch plan, the arbitrary maximum operating time can be changed to 7,7,7,7 and the dispatch plan can be established again. Afterwards, if the dispatch plan according to the changed maximum operating time is classified as a possible dispatch plan, the arbitrary maximum operating time can be changed to 6,6,6,6 and the dispatch plan can be established again. And if the dispatch plan according to the changed maximum operating time is classified as an impossible dispatch plan, the dispatch plan using the maximum operating time before the previous change of 7,7,7,7 can be determined as the first modified dispatch plan. Accordingly, it is possible to search for a value that minimizes the maximum operating time, and the operational efficiency of each vehicle can be maximized.

[0071]

[0072] According to the first embodiment of the present disclosure, in the fourth step (S240), if the dispatch plan is classified as the impossible dispatch plan, the second step (S220) and the third step (S230) are repeated by extending the maximum operating time, but the dispatch plan for the changed maximum operating time can be determined as a second modified dispatch plan.

[0073] Here, since the impossible dispatch plan means that a dispatch plan based on an arbitrary maximum operating time specified by the server (100) is impossible, measures are taken to enable dispatch. That is, the server (100) expands and changes the maximum operating time and additionally proceeds with the second step (S220) and the third step (S230). Accordingly, if the generated dispatch plan is classified as a possible dispatch plan, the possible dispatch plan may be determined as the second modified dispatch plan.

[0074] For example, for 4 vehicles, the server (100) sets the initial arbitrary maximum operating time as 7,7,7,7 and creates a dispatch plan through the second step (S220) and the third step (S230). However, if the dispatch plan is classified as an impossible dispatch plan, the maximum operating time is changed to 8,8,8,8 and the second step (S220) and the third step (S230) are additionally performed. If the generated dispatch plan is classified as an impossible dispatch plan, the maximum operating time is additionally changed to 9,9,9,9 and the second and third steps (S230) are additionally performed. If the generated dispatch plan is classified as a possible dispatch plan, the dispatch plan may be determined as the second modified dispatch plan. That is, the dispatch plan created by specifying the maximum operating time as 9,9,9,9 may be determined as the second modified dispatch plan. Accordingly, it has the effect of enabling delivery with maximum efficiency in dispatches where delivery with four vehicles is not possible.

[0075]

[0076] According to the first embodiment of the present disclosure, if the maximum operating time of each of the dispatched vehicles in the modified dispatch plan exceeds 10 hours per day, additional vehicles may be assigned, and if the maximum operating time of each of the dispatched vehicles in the modified dispatch plan is less than 4 hours per day, the number of vehicles may be reduced.

[0077] Here, the modified dispatch plan may include both the first modified dispatch plan and the second modified dispatch plan.

[0078] Additionally, adding additional vehicles can increase the number of vehicles available in the same area. For example, if delivery is not possible, additional vehicles can be used to make delivery possible. Conversely, if there are too many vehicles available in the same area, the number of vehicles can be reduced.

[0079] For example, if one or more vehicles require operation exceeding 10 hours per day during the maximum operating hours per vehicle according to the modified dispatch plan, the server (100) may assign additional vehicles and then regenerate the vehicle when specifying the initial arbitrary maximum operating hours. In addition, if one or more vehicles require operation less than 4 hours per day during the maximum operating hours per vehicle according to the modified dispatch plan, the server (100) may reduce the number of vehicles and regenerate the vehicle when specifying the initial arbitrary maximum operating hours. As described above, the server (100) establishes a dispatch plan using the number of vehicles and the maximum operating hours per vehicle, thereby enabling delivery to be made with the minimum number of vehicles and the minimum operating hours in the same area.

[0080]

[0081] A dispatch plan generation method performed by a server (100) according to a second embodiment of the present disclosure with reference to FIGS. 4 and 5 may include: a first step of acquiring first region information (510) including a plurality of region designations for dispatched vehicles; a second step of generating second region information (520) associated with the plurality of designated regions; a third step of registering the first region information (510) and the second region information (520) for the dispatched vehicles; and a fourth step of generating a dispatch plan using the registered first region information (510) and the second region information (520).

[0082] Here, the method for creating a dispatch plan may be to designate a vehicle by region, register information by the designated region, and create a dispatch plan based on the registered region information.

[0083]

[0084] According to the second embodiment of the present disclosure, the first region information (510) may be a region in which the dispatch vehicle can deliver, and the second region information (520) may be a region that overlaps among the first region information (510).

[0085] Specifically, the region information is information acquired by the server (100), which may be information entered by each vehicle, information stored in the server (100), or information acquired from the web. In addition, the first region information (510) may be information on regions where delivery is possible for each vehicle, and may be regions for multiple vehicles. In addition, the second region information (520) may separately manage information on an overlapping portion between a region according to the first region information (510) and a region according to another first region information (510). By separately managing the first region information (510) and the second region information (520), the server (100) can maximize the efficiency of product delivery.

[0086] Based on the first region information (510) obtained as described above, second region information (520) is created and managed separately, but management efficiency can be maximized by registering the first region information (510) and the second region information (520) for each dispatched vehicle.

[0087]

[0088] According to the second embodiment of the present disclosure, the step of generating the dispatch plan may generate a first zone dispatch plan using the minimum movement path within the first zone information (510) of each dispatch vehicle.

[0089] Here, each dispatched vehicle may have first zone information (510). The first zone information (510) is information about the zone to which the dispatched vehicle delivers. When generating a delivery plan for the zone, the shortest route within the zone may be searched for. In other words, the delivery may be made using the shortest time and distance. However, the first zone dispatch plan does not utilize the shortest time and distance. Additional steps may be taken to ensure delivery in the shortest time and distance.

[0090]

[0091] According to the second embodiment of the present disclosure, the step of generating the dispatch plan may generate a second zone dispatch plan in which, for vehicles with a running time of 8 hours or more among the first zone dispatch plans, delivery for the second zone information (520) is excluded from the vehicle 1 zone dispatch plan.

[0092] Here, the primary zone dispatch plan may be for a route that delivers via the shortest distance within each zone for each vehicle. Accordingly, the operating time for each vehicle may vary. For vehicles with operating times exceeding 8 hours, the primary zone dispatch plan may be regenerated by excluding dispatches corresponding to the secondary zone information (520).

[0093] For example, if the operation time of the first vehicle in FIG. 5 is 8 hours or more, the existing route has a-1 -> a-2 -> b-1 -> b-2 as the path to deliver a and b, but the delivery of a and b corresponding to the second zone information (520) may be excluded, and delivery may be made through a-3 and b-3, and the dispatch plan generated accordingly may be a second zone dispatch plan. In the second zone dispatch plan according to this, the delivery time is shortened because the delivery locations of the first vehicle are reduced. A detailed description of a and b excluded from delivery will be provided later.

[0094]

[0095] According to the second embodiment of the present disclosure, among the second zone dispatch plans, a first zone including vehicles with a running time of 8 hours or more may allow dispatch of external vehicles.

[0096] Here, the second zone dispatch plan excludes deliveries corresponding to the second zone information (520), but there may be cases where the first vehicle's operating time exceeds 8 hours. As a result, a surplus delivery location (P) may be created for deliveries within the first zone that are canceled or excluded. This will be described in detail later.

[0097]

[0098] According to the second embodiment of the present disclosure, the fourth step of generating the dispatch plan may generate a third zone dispatch plan by additionally dispatching order information of the second zone for vehicles with a running time of less than 8 hours among the first zone dispatch plans.

[0099] Here, the second vehicle may make additional deliveries for deliveries outside of the first zone if the operating time according to the first zone dispatch plan is less than 8 hours and there are no additional deliveries within the first zone of the second vehicle.

[0100] For example, if delivery of a and b is excluded from the first vehicle, additional dispatch for a and b is required. The additional dispatch can be performed by the second vehicle. If the second vehicle has a dispatch plan created through c-1, but the operating time for this is less than 8 hours, additional dispatch for a and b can be performed. In other words, the c-1 route is excluded, and a 3rd zone dispatch plan can be created, which is a dispatch plan that allows delivery of a and b through the c-2 -> c-3 -> c-4 route. According to the 3rd zone dispatch plan, delivery can be performed without any gaps in the delivery destinations within the 2nd zone information (520).

[0101]

[0102] According to the second embodiment of the present disclosure, a vehicle with a running time of less than 4 hours within the third zone dispatch plan may add dispatch of other vehicles to the first zone.

[0103] Here, vehicles with a running time of less than four hours under the third-zone dispatch plan may result in wasted vehicles and operating time. Therefore, additional dispatches may be required.

[0104] Specifically, if the maximum operating time for a second-zone dispatch plan within the first zone for each vehicle exceeds the maximum operating time, there may be delivery destinations where deliveries cannot be made. Consequently, deliveries to these destinations may be dispatched to external vehicles.

[0105] For example, if the operating hours of the first vehicle exceed the limit and a surplus delivery location (P) is created, the surplus delivery location can be handled by a third vehicle with an operating time of less than 4 hours. In other words, the operations of the first vehicle, which has excessive delivery and operating hours, can be distributed to the third vehicle, which has limited delivery and operating hours, thereby maximizing delivery efficiency per vehicle.

[0106] According to the second embodiment of the present disclosure, a first zone including vehicles with a running time of less than 4 hours within the third zone dispatch plan may restrict dispatch of external vehicles.

[0107] Specifically, even if the dispatch plan within the first zone, which is a vehicle-specific zone, has been completed, if a vehicle with a running time of less than 4 hours is included, external vehicles entering the first zone may be restricted.

[0108] For example, entry of external vehicles (E) into Zone 1, which includes the second and third vehicles, may be restricted. Furthermore, entry to the outside from Zone 1, which includes the second and third vehicles, may be permitted.

[0109] When dispatch plans are generated for each of the first to third zone dispatch plans as described above, the corresponding dispatch plans can be generated as the final dispatch plan. The generated final dispatch plan can be recommended to each vehicle.

[0110]

[0111] A dispatch plan generation method performed by a server (100) according to a third embodiment of the present disclosure with reference to FIG. 6 may include a first step of registering region information for a dispatched vehicle (wherein the region information includes information on a preferred region (610) or an avoided region (620); a second step of generating a cost matrix using the region information; a third step of adjusting the cost of the cost matrix using the region information on the preferred region (610) or the avoided region (620); and a fourth step of generating a dispatch plan using the adjusted cost matrix.

[0112] Here, the preferred zone may be information about the zone preferred by each vehicle, and the avoided zone (620) may be information about the zone avoided by each vehicle. For example, when generating a dispatch plan for Gangnam-gu, the first vehicle may set Gaepo-dong, Ilwon-dong, and Segok-dong as the avoided zone (620), and Daechi-dong, Yeoksam-dong, Nonhyeon-dong, and Cheongdam-dong as the preferred zone (610).

[0113] Additionally, the server (100) where the region information is registered can specify the cost according to movement by delivery location and can create a dispatch plan according to the cost.

[0114]

[0115] According to a third embodiment of the present disclosure, the region information is designated for each vehicle, and the cost matrix can designate a cost proportional to the travel distance from an arbitrary delivery location to an adjacent delivery location.

[0116] Here, the preferred zone (610) and avoided zone (620), which are regional information, specify the information registered for each vehicle. Furthermore, as shown in Figure 6, the cost matrix is ​​a shape formed by a path (H) connecting multiple delivery locations (M), with each line having a cost value. The cost may be formed in proportion to the travel distance along the path from the first delivery location to the second delivery location.

[0117]

[0118] According to the third embodiment of the present disclosure, the third step of adjusting the cost may assign a weight to the cost within the avoidance zone (620).

[0119] Here, the cost is assigned to each delivery location in the preferred area (610) and the avoided area (620), and a weight can be assigned to differentiate the avoided area (620) for each vehicle.

[0120] Here, the weight may be assigned to the entire route (H) connected to the delivery location located in the avoided area (620) among the entire cost matrix. As illustrated in FIG. 6, for example, if a route within the preferred area (610) is assigned a cost of 5 per km, a route within the avoided area (620) may be assigned a cost of 25 per km. In other words, a cost five times higher may be assigned. Accordingly, when the server (100) generates a dispatch plan based on costs, it can distinguish between the preferred area (610) and the avoided area (620) for each vehicle and give priority to the delivery location in the preferred area (610).

[0121]

[0122] According to the third embodiment of the present disclosure, the third step of adjusting the cost may, when the preferred area (610) and the avoided area (620) overlap, deduct the cost for the overlapping area by 50%.

[0123] Here, the matrix of the region (b1) where the preferred region (610) and the avoided region (620) overlap is a matrix formed separately from the matrix (a1) of the preferred region (610) and the matrix (c1) of the avoided region. Specifically, the overlapping region (b1) is an avoided region (620), but because it is adjacent to the preferred region (610), it can be a region that can be flexibly delivered, unlike the matrix (c1) of the avoided region.

[0124] Accordingly, some deliveries can be made possible by having a lower cost compared to the matrix of the avoided area (620). For example, if the avoided area cost is 25 per kilometer, the cost of the overlapping area (b1) can be 12.5, which is 50% less than the avoided area cost.

[0125]

[0126] According to a third embodiment of the present disclosure, the third step of adjusting the cost may designate a group of delivery destinations having values ​​lower than the average of the costs as low-cost delivery destinations when there are multiple delivery destinations.

[0127] Specifically, the low-cost delivery location (d1) may be designated by each of the preferred zone matrix (a1), the overlapping zone matrix (b1), and the avoided zone matrix (c1). This is because, when calculating the average of the weighted avoided zone matrix (c1) and the unweighted preferred zone matrix (a1), the cost of the preferred zone matrix (a1) can be designated as significantly lower.

[0128] For example, if multiple delivery destinations with a cost of 1 or less are created within the preferred region matrix (a1), they can be designated as separate low-cost delivery destinations (d1) and the cost can be assigned to adjacent nodes from the low-cost delivery destinations (d1).

[0129]

[0130] According to a third embodiment of the present disclosure, the third step of adjusting the cost may recover the cost weight for the overlapping area when the dispatch vehicle enters the overlapping area from the preferred area (610) and delivers according to the dispatch plan.

[0131] Specifically, in the step of generating a dispatch plan for a vehicle departing from a preferred zone (610), there may be cases where the entry cost into an overlapping zone is lower than that of entering the preferred zone (610). In such cases, when calculating the cost for the next delivery destination of a vehicle that has entered the overlapping zone, a weight may be recovered so that the cost for the overlapping zone has the same cost as that of the preferred zone (610). For example, if a cost of 5 per km is assigned in the preferred zone (610) and a cost of 12.5 per km is assigned in the overlapping zone, when a dispatched vehicle enters the overlapping zone, the cost in the overlapping zone may be changed to 5 per km to generate a dispatch plan. In such cases, delivery from a delivery destination within the preferred zone (610) to a delivery destination in a very close overlapping zone is possible, and since additional dispatches are made to adjacent delivery destinations, delivery efficiency can be maximized in the overall dispatch plan.

[0132]

[0133] According to the third embodiment of the present disclosure, the fourth step of generating the dispatch plan may generate a dispatch plan that minimizes the cost, and if the costs are the same, the dispatch plan may be generated by selecting a priority in order of the shortest travel time.

[0134] As described above, the dispatch plan generation method of the present disclosure generates dispatch plans based on cost. At this time, multiple dispatch plans may be generated, and the most efficient dispatch plan must be selected from among them. To this end, the server (100) may select dispatch plans with the same cost and prioritize them based on the shortest vehicle travel time among the selected dispatch plans. In other words, plans with the same cost may be affected by various variables, such as travel distance or zone travel. Among these, shorter travel times can maximize efficiency for each vehicle.

[0135] For example, among the z dispatch plan and the x dispatch plan having the same cost, the z dispatch plan is formed so that delivery is made only within the preferred zone (610), and when the x dispatch plan enters an overlapping zone from the preferred zone (610), the x dispatch plan that entered the overlapping zone with a high cost compared to the preferred zone (610) may have a much shorter operation time than the z dispatch plan that only moves within the preferred zone (610). Specifically, when entering an overlapping zone from the preferred zone (610), since the comparative cost is high, entry is only possible if the travel distance per delivery location is very close. Accordingly, the travel time can be very short. Using this method, it may be possible to create a dispatch plan with a short travel distance per delivery location and a short operation time.

[0136]

[0137] According to a third embodiment of the present disclosure, the third step of adjusting the cost may set an obstruction path (including a river, a construction site, and a road with heavy traffic congestion) that obstructs the movement of vehicles within the area, and the step of generating the dispatch plan may generate a dispatch plan with the highest priority among dispatch plans excluding dispatch plans including the obstruction path from dispatch plans having the priority as a final dispatch plan.

[0138] Here, obstruction paths include rivers, construction sites, and heavily congested roads—anything that impedes vehicle movement.

[0139] Additionally, the highest priority dispatch plan can be the highest priority dispatch plan among the prioritized dispatch plans. That is, it can be the dispatch plan with the lowest cost, shortest travel time, and no obstructed routes.

[0140] In other words, because Cost lacks information about obstructed routes, it may have travel times disproportionate to the delivery distance. To prevent this, separate obstructed routes are set up, and these can be used to minimize delivery time and distance.

[0141] Finally, the highest priority dispatch plan excluding obstructed routes is finally generated and can be recommended for each vehicle.

[0142]

[0143] A method for generating a dispatch plan using a clustering method according to a fourth embodiment of the present disclosure with reference to FIGS. 7 and 8 may include a first step of generating clusters in which a plurality of order information are grouped; a second step of determining priorities between the clusters; a third step of generating a dispatch plan for each cluster; a fourth step of regenerating the dispatch plan based on the dispatch plan for each cluster and the priorities; and a fifth step of adjusting the dispatch plan using area information for each dispatched vehicle.

[0144] Here, clusters may be formed by grouping related delivery locations (e.g., nearby delivery locations, delivery locations in the same district, etc.). If the number of delivery locations increases significantly, the server (100) may become overloaded due to increased computational load. To prevent this, clusters may be formed and processed.

[0145] Additionally, the first step of creating a cluster may be to form a grouped cluster, which may be a grouping of multiple order information (including origin and destination), and the clusters may be formed by region.

[0146] Additionally, the second step in determining priorities may involve assigning priorities to each generated cluster. Specifically, the cluster containing the origin may be given higher priority, followed by clusters closer to it, which may then be prioritized. In other words, clusters may be prioritized in order of proximity, but this is not a limitation.

[0147] Additionally, the third step of generating a dispatch plan may involve generating dispatch plans for each pre-defined cluster based on its internal delivery destination. In other words, multiple clusters may each have their own dispatch plan.

[0148] Additionally, the fourth step of regenerating the dispatch plan may be to regenerate the dispatch plan based on the inter-cluster priorities and the cluster-specific dispatch plan. In other words, it may be a complete delivery plan that includes both intra-cluster planning and inter-cluster priorities.

[0149] Additionally, the fifth step of adjusting the dispatch plan may involve generating a final delivery plan through additional adjustments based on vehicle-specific area information in the overall delivery plan. The final delivery plan generated as described above may be recommended by the server (100) for each vehicle.

[0150]

[0151] According to the fourth embodiment of the present disclosure, the first step of generating the clusters may group the clusters by delivery locations having a close straight-line distance from the delivery locations of the order information, and may group the clusters by specifying the maximum value of the weight or volume of the products delivered within the cluster.

[0152] Here, clusters are formed using the straight-line distance between delivery points, and may be formed by limiting the maximum cluster size.

[0153] Additionally, grouping can be done by limiting the maximum weight or volume of products shipped within a cluster. This restriction prevents the cluster from expanding infinitely. Furthermore, it can be controlled to ensure an appropriate size.

[0154]

[0155] According to the fourth embodiment of the present disclosure, the second step of determining the priority may determine the cluster closest in a straight line distance from the warehouse from which the dispatched vehicle departs as the first priority, and the closest cluster among the n-rank clusters may be determined as the n+1 priority.

[0156] Here, a warehouse may be a place where delivery items are gathered. That is, it may be a place where incoming delivery orders are stored and shipped to delivery vehicles with invoices attached. In other words, it may be a place a dispatch vehicle must pass through to load the items.

[0157] Additionally, the cluster closest in straight line to the warehouse may be ranked first, and the cluster closest to the first-ranked cluster may be designated as the second-ranked cluster. For example, referring to Figure 7(b), cluster a2, which is closest to the warehouse, may be ranked first, and cluster b2, which is closest to cluster a2, may be ranked second. Clusters are prioritized in this order. Furthermore, the distance from the warehouse to which the delivery vehicle must return may be taken into account when assigning priorities. For example, clusters that are more than 100 km from the warehouse may be excluded from the ranking.

[0158]

[0159] According to the fourth embodiment of the present disclosure, the third step of generating the dispatch plan generates the dispatch plan in the direction of the n+1st rank cluster from the nth rank cluster within the cluster, and can generate the dispatch plan as a route with the minimum travel distance within the cluster.

[0160] The third step in generating a dispatch plan here may involve generating dispatch plans for each delivery location within a cluster. This dispatch plan may be generated toward the next highest-ranking cluster. Alternatively, the dispatch plan may be formed so that the last dispatch from the current highest-ranking cluster ends in the next highest-ranking cluster.

[0161] For example, as shown in Fig. 7(c), the dispatch plan within the first-ranked cluster, a2, may proceed toward the second-ranked cluster, b2, with the final delivery destination being formed near b2. Furthermore, the dispatch plan within the second-ranked cluster, b2, may be generated toward the third-ranked cluster, d2, with the final delivery destination being formed near the fourth-ranked cluster, c2.

[0162]

[0163] According to the fourth embodiment of the present disclosure, the fourth step of regenerating the dispatch plan may generate the final dispatch plan by designating the delivery location of the n+1st rank cluster with the shortest travel distance from the final destination of the nth rank cluster as the departure location.

[0164] The dispatch plan generation method of the present disclosure may generate an optimized dispatch plan by minimizing delivery distance and delivery time. To this end, when generating a dispatch plan within a current cluster, the dispatch plan is generated in a direction closer to the next cluster. Similarly, when moving from the last delivery location in the current cluster to the next cluster, the closest delivery location can be generated as the first delivery location in the next cluster. In other words, when a dispatched vehicle moves between clusters, it is designed to travel the shortest distance, thereby optimizing entry into the next cluster.

[0165]

[0166] According to the fourth embodiment of the present disclosure, the fifth step of adjusting the dispatch plan may include the region information including a preferred region (610) and an avoided region (620), and may exclude delivery locations outside the preferred region (610) from the dispatch plan.

[0167] Here, the zone information may be vehicle-specific zone information. That is, the zone desired by the vehicle may be a preferred zone (610), and the area avoided may be an avoided zone (620). Based on the zone information, delivery locations within the preferred zone (610) may be included in the dispatch plan, and conversely, delivery locations outside the preferred zone (610) may be excluded from the dispatch plan.

[0168] For example, referring to FIG. 8, the dispatch plan is executed in the order of 1st cluster (a2), 2nd cluster (b2), 3rd cluster (d2), and 4th cluster (c2), and the dispatch plan may be generated from a delivery location excluding S2, which is an avoidance area (620).

[0169]

[0170] According to the fourth embodiment of the present disclosure, the fifth step of adjusting the dispatch plan may exclude a delivery location that includes the avoidance area (620) from the dispatch plan.

[0171] Here, the dispatch plan can be created by excluding delivery locations that include the avoidance zone (620).

[0172] For a specific example, referring to Fig. 8, it may be possible to establish a dispatch plan excluding delivery to a delivery location (N2) in an avoidance area (620), but is not limited thereto.

[0173]

[0174] According to the fourth embodiment of the present disclosure, the fifth step of adjusting the dispatch plan may include a delivery location located on the movement route in the avoided area (620), when passing through a delivery location that includes the avoided area (620) excluded from the dispatch plan.

[0175] The method for generating a dispatch plan using the clustering method of the present disclosure may exclude dispatches to delivery locations (S2) within the avoided zone. However, in the overall dispatch plan, there may be instances where dispatched vehicles pass through the avoided zone (620). In such cases, the dispatched vehicle may additionally perform deliveries to the delivery location (S2) within the avoided zone (620).

[0176] For example, referring to Fig. 8, the overall dispatch plan carries out deliveries in the order of a2 -> b2 -> d2 -> c2, and when moving from cluster b2 to cluster d2, it moves via the shortest distance delivery location (M2) in cluster d2. At this time, delivery (N2) to a delivery location in an undesirable area (S2) may be additionally carried out. In other words, when moving along the shortest route (M2), delivery may be carried out to a nearby delivery location (N2). This delivery to a delivery location (N2) can minimize the delivery time and delivery distance in the dispatch plan of other vehicles that must deliver to the delivery location (N2).

[0177] As described above, the optimized dispatch plan may be determined as the final dispatch plan, and the determined final dispatch plan may be recommended for each vehicle.

[0178]

[0179] The first to fourth embodiments described above may be implemented singly or in combination.

[0180]

[0181] FIG. 9 is a drawing for explaining a server (100) according to one embodiment of the present disclosure.

[0182] The configuration of the server (100) illustrated in FIG. 9 is merely an example that is simplified. In the first to fourth embodiments of the present disclosure, the server (100) may include other configurations for performing the computing environment of the server (100), and only some of the disclosed configurations may constitute the server (100).

[0183] The server (100) may include a processor (110), memory (130), and network unit (150).

[0184] The processor (110) may be configured with one or more cores, and may include a processor for data analysis and deep learning, such as a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU) of a server. The processor (110) may read a computer program stored in the memory (130) and perform data processing for machine learning according to an embodiment of the present disclosure. According to an embodiment of the present disclosure, the processor (110) may perform operations for learning a neural network. The processor (110) may perform calculations for learning a neural network, such as processing input data for learning in deep learning (DL), extracting features from input data, calculating errors, and updating weights of a neural network using backpropagation. At least one of the CPU, GPGPU, and TPU of the processor (110) may process learning of a network function. For example, a CPU and a GPGPU can work together to learn network functions and classify data using network functions. Furthermore, in one embodiment of the present disclosure, processors from multiple servers can be used together to learn network functions and classify data using network functions. Furthermore, a computer program executed on a server according to one embodiment of the present disclosure may be a CPU, GPGPU, or TPU executable program.

[0185] According to one embodiment of the present disclosure, the memory (130) can store any form of information generated or determined by the processor (110) and any form of information received by the network unit (150).

[0186] According to one embodiment of the present disclosure, the memory (130) may include at least one type of storage medium among a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk. The server (100) may also operate in relation to web storage that performs the storage function of the memory (130) on the Internet. The description of the above-described memory is merely an example, and the present disclosure is not limited thereto.

[0187] The network unit (150) according to one embodiment of the present disclosure can use various wired communication systems such as a public switched telephone network (PSTN), xDSL (x Digital Subscriber Line), RADSL (Rate Adaptive DSL), MDSL (Multi Rate DSL), VDSL (Very High Speed ​​DSL), UADSL (Universal Asymmetric DSL), HDSL (High Bit Rate DSL), and a local area network (LAN).

[0188] In addition, the network unit (150) presented in this specification can use various wireless communication systems such as CDMA (Code Division Multi Access), TDMA (Time Division Multi Access), FDMA (Frequency Division Multi Access), OFDMA (Orthogonal Frequency Division Multi Access), SC-FDMA (Single Carrier-FDMA) and other systems.

[0189] In the present disclosure, the network unit (150) may be configured regardless of the communication mode, such as wired or wireless, and may be configured as various communication networks, such as a personal area network (PAN) and a wide area network (WAN). In addition, the network may be the well-known World Wide Web (WWW), and may also utilize a wireless transmission technology used for short-distance communication, such as infrared (IrDA: Infrared Data Association) or Bluetooth.

[0190]

[0191] FIG. 10 is a general schematic diagram of an exemplary computing environment in which embodiments of the present disclosure may be implemented.

[0192] Although the present disclosure has been described above as being generally implemented by a server, those skilled in the art will appreciate that the present disclosure may be implemented in combination with computer-executable instructions and / or other program modules that may be executed on one or more computers and / or as a combination of hardware and software.

[0193] Generally, program modules include routines, programs, components, data structures, and the like that perform specific tasks or implement specific abstract data types. Furthermore, those skilled in the art will appreciate that the methods of the present disclosure can be implemented with other computer system configurations, including single-processor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld servers, microprocessor-based or programmable consumer electronics, and the like, each of which may be operatively connected to one or more associated devices.

[0194] The described embodiments of the present disclosure can also be practiced in distributed computing environments, where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0195] Computers typically include a variety of computer-readable media. Computer-readable media can be any media that can be accessed by a computer, and includes both volatile and nonvolatile media, transitory and non-transitory media, removable and non-removable media. By way of example, and not limitation, computer-readable media can include computer-readable storage media and computer-readable transmission media. Computer-readable storage media includes both volatile and nonvolatile media, transitory and non-transitory media, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be accessed by a computer and used to store the desired information.

[0196] Computer-readable transmission media typically includes any information delivery media that embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism. The term modulated data signal means a signal that has one or more of its characteristics set or changed so as to encode information in the signal. By way of example, and not limitation, computer-readable transmission media includes wired media, such as a wired network or direct-wired connection, and wireless media, such as acoustic, RF, infrared, or other wireless media. Combinations of any of the above are also intended to be included within the scope of computer-readable transmission media.

[0197] An exemplary environment (1100) implementing various aspects of the present disclosure is illustrated, including a computer (1102) comprising a processing unit (1104), system memory (1106), and a system bus (1108). The system bus (1108) connects system components, including but not limited to the system memory (1106), to the processing unit (1104). The processing unit (1104) may be any of a variety of commercially available processors. Dual processors and other multiprocessor architectures may also be utilized as the processing unit (1104).

[0198] The system bus (1108) may be any of several types of bus structures that may be additionally interconnected to a memory bus, a peripheral bus, and a local bus using any of a variety of commercial bus architectures. The system memory (1106) includes read-only memory (ROM) (1110) and random access memory (RAM) (1112). A basic input / output system (BIOS) is stored in non-volatile memory (1110), such as ROM, EPROM, or EEPROM, and includes basic routines that help transfer information between components within the computer (1102), such as during start-up. The RAM (1112) may also include high-speed RAM, such as static RAM, for caching data.

[0199] The computer (1102) also includes an internal hard disk drive (HDD) (1114) (e.g., EIDE, SATA) - which may also be configured for external use within a suitable chassis (not shown), a magnetic floppy disk drive (FDD) (1116) (e.g., for reading from or writing to a removable diskette (1118)), and an optical disk drive (1120) (e.g., for reading from or writing to a CD-ROM disk (1122) or other high-capacity optical media such as a DVD). The hard disk drive (1114), the magnetic disk drive (1116), and the optical disk drive (1120) may be connected to the system bus (1108) by a hard disk drive interface (1124), a magnetic disk drive interface (1126), and an optical drive interface (1128), respectively. The interface (1124) for implementing an external drive includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

[0200] These drives and their associated computer-readable media provide non-volatile storage of data, data structures, computer-executable instructions, and the like. In the case of the computer (1102), the drives and media correspond to storing any data in a suitable digital format. While the description of computer-readable media above refers to HDDs, removable magnetic disks, and removable optical media such as CDs or DVDs, those skilled in the art will appreciate that other types of media readable by a computer, such as zip drives, magnetic cassettes, flash memory cards, cartridges, and the like, may also be used in the exemplary operating environment, and that any such media may contain computer-executable instructions for performing the methods of the present disclosure.

[0201] A number of program modules, including an operating system (1130), one or more application programs (1132), other program modules (1134), and program data (1136), may be stored in the drive and RAM (1112). All or portions of the operating system, applications, modules, and / or data may also be cached in RAM (1112). It will be appreciated that the present disclosure may be implemented in various commercially available operating systems or combinations of operating systems.

[0202] A user may enter commands and information into the computer (1102) via one or more wired / wireless input devices, such as a keyboard (1138) and a pointing device such as a mouse (1140). Other input devices (not shown) may include a microphone, an IR remote control, a joystick, a game pad, a stylus pen, a touch screen, and the like. These and other input devices are often connected to the processing unit (1104) via an input device interface (1142) that is connected to the system bus (1108), but may be connected by other interfaces such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, and the like.

[0203] A monitor (1144) or other type of display device is also connected to the system bus (1108) via an interface, such as a video adapter (1146). In addition to the monitor (1144), the computer typically includes other peripheral output devices (not shown), such as speakers, a printer, and so on.

[0204] The computer (1102) may operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s) (1148), via wired and / or wireless communications. The remote computer(s) (1148) may be a workstation, a computing device computer, a router, a personal computer, a portable computer, a microprocessor-based entertainment device, a peer device, or other conventional network node, and generally include many or all of the components described for the computer (1102), although for simplicity, only the memory storage device (1150) is shown. The logical connections shown include wired / wireless connections to a local area network (LAN) (1152) and / or a larger network, such as a wide area network (WAN) (1154). Such LAN and WAN networking environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which may be connected to a worldwide computer network, such as the Internet.

[0205] When used in a LAN networking environment, the computer (1102) is connected to a local network (1152) via a wired and / or wireless communication network interface or adapter (1156). The adapter (1156) may facilitate wired or wireless communications to the LAN (1152), which may also include a wireless access point installed therein for communicating with the wireless adapter (1156). When used in a WAN networking environment, the computer (1102) may include a modem (1158), be connected to a communications computing device on the WAN (1154), or have other means of establishing communications over the WAN (1154), such as via the Internet. The modem (1158), which may be internal or external and wired or wireless, is connected to the system bus (1108) via a serial port interface (1142). In a networked environment, program modules or portions thereof described for the computer (1102) may be stored in a remote memory / storage device (1150). It will be appreciated that the network connections depicted are exemplary and other means of establishing a communications link between the computers may be used.

[0206] The computer (1102) operates to communicate with any wireless device or object that is arranged and operates via wireless communication, such as a printer, a scanner, a desktop and / or portable computer, a portable data assistant (PDA), a communication satellite, any equipment or location associated with a radio-detectable tag, and a telephone. This includes at least Wi-Fi and Bluetooth wireless technologies. Accordingly, the communication may be a predefined structure as in a conventional network, or may simply be an ad hoc communication between at least two devices.

[0207] Wi-Fi (Wireless Fidelity) enables connections to the Internet and other devices without wires. Wi-Fi is a wireless technology that allows devices, such as computers, to send and receive data anywhere within the coverage area of ​​a base station, both indoors and outdoors, similar to cell phones. Wi-Fi networks use wireless technologies called IEEE 802.11 (a, b, g, etc.) to provide secure, reliable, and high-speed wireless connections. Wi-Fi can be used to connect computers to each other, to the Internet, and to wired networks (using IEEE 802.3 or Ethernet). Wi-Fi networks can operate in the unlicensed 2.4 and 5 GHz radio bands, at data rates of, for example, 11 Mbps (802.11a) or 54 Mbps (802.11b), or in products that include both bands (dual-band).

[0208] Those skilled in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips referenced in the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0209] Those skilled in the art will appreciate that the various illustrative logical blocks, modules, processors, means, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, various forms of programs or design code (referred to herein, for convenience, as software), or a combination of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0210] The various embodiments presented herein can be implemented as a method, apparatus, or article of manufacture using standard programming and / or engineering techniques. The term article of manufacture includes a computer program, carrier, or media accessible from any computer-readable storage device. For example, computer-readable storage media include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CDs, DVDs, etc.), smart cards, and flash memory devices (e.g., EEPROMs, cards, sticks, key drives, etc.). Furthermore, various storage media presented herein include one or more devices and / or other machine-readable media for storing information.

[0211] It should be understood that the specific order or hierarchy of steps in the presented processes is merely an example of exemplary approaches. It should be understood that the specific order or hierarchy of steps in the processes may be rearranged within the scope of the present disclosure based on design priorities. The appended method claims provide elements of various steps in a sample order, but are not intended to be limited to the specific order or hierarchy presented.

[0212] The description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments disclosed herein, but is to be construed in the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating a dispatch plan performed by a server, A first step of obtaining first zone information including zone designation for each of a plurality of dispatched vehicles; A second step of generating second region information associated with the plurality of regions specified above; A third step of registering first region information and second region information for the above dispatched vehicle; and A fourth step of generating a dispatch plan using the registered first region information and the second region information; including; How to create a dispatch plan.

2. In paragraph 1, The above first region information is, The above dispatch vehicle's delivery area is The above second region information is: Among the above first region information, the overlapping region is How to create a dispatch plan.

3. In paragraph 2, The steps for generating the above dispatch plan are: Generating a first zone dispatch plan using the minimum movement path within the first zone information of each of the above dispatched vehicles. How to create a dispatch plan.

4. In paragraph 3, The fourth step above is, Among the above 1st zone dispatch plans, vehicles with a running time exceeding the first threshold are: In the above first zone dispatch plan, a second zone dispatch plan is created excluding delivery for the second zone information. How to create a dispatch plan.

5. In paragraph 4, Among the above 2nd zone dispatch plans, the 1st zone that includes vehicles with a running time exceeding the 1st threshold is Allowing dispatch of external vehicles, How to create a dispatch plan.

6. In paragraph 4, The fourth step above is, Among the above 1st zone dispatch plans, vehicles whose operating time is less than the first threshold are: By adding the order information of the above second region, a third region dispatch plan is created. How to create a dispatch plan.

7. In paragraph 1, The above first region information and the above second region information, Includes a preferred area or an avoided area, wherein the preferred area and the avoided area include cost information, The third step above is, Adjusting the cost based on the above cost information, How to create a dispatch plan.

8. In paragraph 7, The third step above is, Weighting the costs within the above-mentioned avoidance zone, How to create a dispatch plan.

9. In paragraph 8, The third step above is, If the above-mentioned aversion zone and the above-mentioned preferred zone overlap, Deduct a certain amount of cost for the above overlapping areas, How to create a dispatch plan.

10. In paragraph 9, The fourth step above is, Create a dispatch plan that minimizes the above cost, If the above costs are the same, Generate the above dispatch plan by prioritizing the optimal route. How to create a dispatch plan.

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