Engineering mechanical equipment leasing intelligent scheduling system and method, medium, program product and terminal

Abstract

The invention provides an intelligent scheduling system and method for engineering mechanical equipment leasing, a medium, a program product and a terminal, and the system achieves the mutual cooperation of a complete hosting algorithm, a warehouse allocation algorithm and a stowage algorithm through the construction of the intelligent scheduling system of an order screening module, a warehouse allocation module, a stowage module and a transportation execution module. The processes of order screening, warehouse selection, vehicle selection, task issuing and the like in leasing equipment scheduling are automatically screened and executed by the system, so that the execution efficiency of the scheduling system is improved, the warehouse and the vehicle which most conform to conditions are matched for the current order through the warehouse allocation algorithm and the stowage algorithm, the time cost and the expense cost are saved, and the efficiency is improved. And the requirement of an actual scheduling scene is met.

Description

Technical Field

[0001] This application relates to the technical field of intelligent scheduling, and particularly to an intelligent scheduling system, method, medium, program product and terminal for the lease of engineering machinery equipment. Background Art

[0002] In the logistics and distribution link of the current equipment leasing industry, the scheduling of operation tasks mainly relies on the manual experience and manual operation of dispatchers. Its conventional workflow is as follows: Dispatchers receive equipment lease order information from different customers through methods such as phone calls, text messages or instant messaging software, including the type and quantity of leased equipment, pick-up and delivery locations, expected time, etc. Subsequently, the dispatcher needs to rely on personal judgment of vehicle location, road conditions, customer importance and rough empirical distance, and through manual marking, listing on a whiteboard or using simple spreadsheet tools, match and combine vehicles with orders, and plan a rough delivery route for each vehicle. The entire scheduling process highly depends on the personal experience and on-the-spot judgment of the dispatcher, belonging to a typical "human brain calculation" and "manual allocation" mode.

[0003] The above manual scheduling mode relying on manual experience is difficult to meet the requirements of high efficiency and accuracy in modern lease scheduling, and has the following disadvantages:

[0004] (1) Low efficiency and slow response: When facing a large number of concurrent orders, manually matching vehicles and routes takes several hours or even longer, and it is impossible to achieve a quick response, making it difficult to handle emergency orders or temporary changes.

[0005] (2) High transportation cost: Due to the limitations of human computing power, dispatchers cannot comprehensively consider all constraints within a short time, and the formulated scheduling plan is often only "feasible" rather than "optimal", which easily leads to problems such as circuitous transportation routes, high vehicle empty load rates, and waste of transport capacity resources, thus driving up the operating cost. Summary of the Invention

[0006] In view of the above-mentioned disadvantages of the prior art, the purpose of this application is to provide an intelligent scheduling system, method, medium, program product and terminal for the lease of engineering machinery equipment, which is used to solve the problems of low efficiency, slow response and high transportation cost in traditional manual scheduling.

[0007] To achieve the above and other related objectives, the first aspect of this application provides an intelligent dispatching system for construction machinery equipment leasing, comprising: an order screening module, a warehousing module, a loading module, and a transportation execution module; wherein, the order screening module is used to screen several order demands for construction machinery equipment based on a fully managed model to obtain several target order demands that meet preset fully managed conditions; the warehousing module is used to calculate corresponding shipping warehouse information and generate corresponding outbound information for several target order demands using a warehousing algorithm combined with construction machinery equipment warehouse information; the loading module is used to generate outbound transportation dispatching information and outbound information based on the shipping warehouse information and outbound information corresponding to each target order demand using a loading algorithm; and generate return transportation dispatching information based on return information and shipping warehouse information within each target order demand using a loading algorithm; the transportation execution module is used to send transportation execution instructions to the logistics transportation system according to the outbound transportation dispatching information or the return transportation dispatching information to arrange vehicles to transport construction machinery equipment.

[0008] In some embodiments of the first aspect of this application, the process of filtering several order demands for construction machinery equipment based on a fully managed model to obtain several target order demands that meet preset fully managed conditions includes: configuring preset fully managed conditions in the fully managed model; the preset fully managed conditions include: the difference between the estimated entry time and the approval time, the distance between the optimal warehouse and the delivery location, the optimal warehouse inventory fulfillment form, the maximum number of orders automatically dispatched by the optimal warehouse on the current day, and the optimal vehicle; inputting several order demands for construction machinery equipment into the fully managed model for matching, and if the current order demand meets the preset fully managed conditions, then the current order demand is a target order demand that meets the preset fully managed conditions.

[0009] In some embodiments of the first aspect of this application, the process of calculating the corresponding shipping warehouse information for several target order demands using a warehousing algorithm includes: calculating the actual driving path distance between the target order demand and each warehouse in the construction machinery equipment warehouse information based on the receiving address information in the target order demand and the warehouse information; sorting the actual driving path distances in ascending order, and selecting several warehouses that meet the preset nearest principle based on the sorting results; and matching the equipment list information corresponding to the several warehouses with the target order demand to obtain the shipping warehouse information and outbound information corresponding to the target order demand.

[0010] In some embodiments of the first aspect of this application, the step of generating shipping transportation scheduling information based on the shipping warehouse information and outbound information corresponding to each target order demand using a loading algorithm includes: calculating several shipping vehicle loading information based on the shipping warehouse information and outbound information of several target order demands using a loading algorithm; the shipping vehicle loading information includes: shipping vehicle consolidation mode, delivery route planning, and shipping transportation cost; filtering based on the transportation cost corresponding to the several vehicle loading information to select shipping vehicle loading information that meets the preset cost requirements, and using the shipping vehicle consolidation mode and delivery route planning of the vehicle loading information that meets the preset cost requirements as the shipping transportation scheduling information.

[0011] In some embodiments of the first aspect of this application, the step of generating exit transportation scheduling information based on exit information and shipping warehouse information within each target order demand using a loading algorithm specifically includes: calculating several exit vehicle loading information based on exit information and shipping warehouse information of several target order demands using a loading algorithm; the exit vehicle loading information includes: exit vehicle consolidation mode, exit route planning, and exit transportation cost; filtering based on the corresponding transportation cost among the several vehicle loading information to select exit vehicle loading information that meets preset cost requirements, and using the exit vehicle consolidation mode and exit route planning of the vehicle loading information that meets the preset cost requirements as exit transportation scheduling information.

[0012] In some embodiments of the first aspect of this application, the process of generating exit transportation scheduling information based on exit information and shipping warehouse information within each target order demand using a loading algorithm includes: matching the exit time in the exit information of the current target order demand with the current time; if the exit time and the current time are successfully matched, generating exit transportation scheduling information for the current target order demand based on the exit time and shipping warehouse information.

[0013] To achieve the above and other related objectives, a second aspect of this application provides an intelligent scheduling method for construction machinery equipment leasing, applied to the aforementioned intelligent scheduling system for construction machinery equipment leasing. The method includes: filtering several order demands for construction machinery equipment based on a fully managed model to obtain several target order demands that meet preset fully managed conditions; calculating corresponding shipping warehouse information and generating corresponding outbound information for the several target order demands using a warehouse allocation algorithm combined with construction machinery equipment warehouse information; generating shipping transportation scheduling information using a loading algorithm based on the shipping warehouse information and outbound information corresponding to each target order demand; and generating return transportation scheduling information using a loading algorithm based on the return information and shipping warehouse information within each target order demand; and sending transportation execution instructions to the logistics transportation system according to the shipping transportation scheduling information or the return transportation scheduling information to arrange vehicle transportation of the construction machinery equipment.

[0014] To achieve the above and other related objectives, a third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the intelligent scheduling method for engineering machinery equipment leasing.

[0015] To achieve the above and other related objectives, a fourth aspect of this application provides a computer program product, which includes computer program code. When the computer program code is run on a computer, the computer implements the intelligent scheduling method for engineering machinery equipment leasing.

[0016] To achieve the above and other related objectives, a fifth aspect of this application provides an electronic terminal, including a memory, a processor, and a computer program stored in the memory; the processor executes the computer program to implement the intelligent scheduling method for engineering machinery equipment leasing.

[0017] As described above, the intelligent dispatching system, method, medium, program product, and terminal for engineering machinery equipment rental of this application have the following beneficial effects:

[0018] (1) This application uses a fully managed model to filter out orders that meet the conditions of full management, reducing the workload of manual scheduling and avoiding human error. Especially when dealing with complex tasks, the system can efficiently complete task allocation.

[0019] (2) The warehouse allocation module and the load allocation module of this application intelligently optimize the route and load allocation, reduce the empty running and waiting time of the transport vehicle, and reduce fuel costs and transportation costs. Attached Figure Description

[0020] Figure 1The diagram shown is a structural schematic of an intelligent dispatching system for engineering machinery equipment rental according to an embodiment of this application.

[0021] Figure 2 The diagram shows the model parameters of the order filtering module in one embodiment of this application.

[0022] Figure 3 The diagram shown is a schematic of the loading module in one embodiment of this application.

[0023] Figure 4 The diagram shown is a schematic representation of a transport execution module in one embodiment of this application.

[0024] Figure 5 The diagram shown is a flowchart illustrating an intelligent scheduling method for engineering machinery equipment leasing according to an embodiment of this application.

[0025] Figure 6 The diagram shown is a structural schematic of an electronic terminal according to an embodiment of this application. Detailed Implementation

[0026] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0027] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," and "holding" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0028] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0029] In the embodiments of this application, terms such as "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. For example, "first soil quality data" and "second soil quality data" are used only to distinguish different soil quality data and do not limit their order. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or execution order, and that terms such as "first" and "second" do not necessarily imply that they are different.

[0030] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the invention.

[0031] To facilitate understanding of the embodiments of this application, firstly, in conjunction with Figure 1 Detailed explanation. Figure 1 A schematic diagram of the structure of an intelligent dispatching system 100 for engineering machinery equipment leasing, according to an embodiment of the present invention, is shown. The system includes:

[0032] The module comprises an order filtering module 101, a warehousing module 102, a loading module 103, and a transportation execution module 104, wherein:

[0033] The order screening module 101 is used to screen several order requirements for construction machinery and equipment based on a fully managed model to obtain several target order requirements that meet the preset fully managed conditions.

[0034] In this embodiment, the engineering machinery equipment includes various types of heavy machinery, widely used in construction, road, bridge, and mining projects. The types of engineering machinery equipment include, but are not limited to: scissor lifts, boom lifts, spider lifts, and rail-mounted aerial work platforms; among them, scissor lifts (also known as scissor-lift aerial work platforms) and boom lifts (such as boom cranes and lifting boom trucks) are common engineering machinery equipment, mainly used for high-altitude operations and material handling. Scissor lifts provide vertical lifting capabilities through their scissor-like structure, suitable for high-altitude operations in confined spaces, and have advantages such as good stability and ease of operation. Boom lifts employ a telescopic boom structure, enabling a wider operating range and suitable for tasks such as working at heights, hoisting, and moving heavy objects. With technological advancements, these devices increasingly emphasize improved operational safety, automation, and energy-saving and environmental performance, and are widely used in various construction scenarios.

[0035] It should be noted that the order requirements include, but are not limited to, user personal information, the expected start time of use of the construction machinery and equipment, the expected end time of use of the construction machinery and equipment, delivery address information, equipment type, equipment quantity, and alternative equipment types.

[0036] The parameters for both the equipment type and alternative equipment types are specifically designed for the application scenarios of the construction machinery, including: equipment power source, equipment manufacturer, equipment control method, and equipment power. The specific parameters can be selected based on actual needs and circumstances, and are not limited here.

[0037] For example, the equipment type and alternative equipment type parameters in a user's order request may include: equipment power source: electric; backup equipment power source: diesel; manufacturer: XCMG; backup manufacturer: Genie; equipment control method: unmanned; backup equipment control method: manned; backup equipment power: 800W; equipment power: 400W, etc.

[0038] In one embodiment, the process of filtering several order demands for construction machinery equipment based on a fully managed model to obtain several target order demands that meet preset fully managed conditions includes: configuring preset fully managed conditions in the fully managed model; the preset fully managed conditions include: the difference between the estimated arrival time and the approval time, the distance between the optimal warehouse and the delivery location, the optimal warehouse inventory fulfillment form, the maximum number of orders automatically dispatched by the optimal warehouse on the current day, and the optimal vehicle; inputting several order demands for construction machinery equipment into the fully managed model for matching, and if the current order demand meets the preset fully managed conditions, then the current order demand is a target order demand that meets the preset fully managed conditions.

[0039] In this embodiment, before intelligent scheduling, user-submitted order requests need to be screened to determine if they meet preset fully managed conditions. The order requests are then input into the fully managed model, which contains preset fully managed conditions. These preset conditions include multiple preset parameters, such as... Figure 2 As shown, the specific components include: the difference between order submission time and expected entry time, the distance between the optimal warehouse and the delivery location, the optimal warehouse inventory fulfillment form, the optimal warehouse warehouse, the maximum number of orders automatically scheduled for the optimal warehouse on the current day, and the optimal vehicle.

[0040] It should be noted that the maximum number of orders automatically scheduled for the best warehouse on a given day is automatically refreshed to a preset maximum value at 0:00 every day. When an order is shipped from this best warehouse, the maximum number of orders automatically scheduled for the best warehouse on a given day is automatically reduced by 1 until it reaches 0.

[0041] Furthermore, the order demand is filtered through the following process: First, the difference between the current time and the estimated start time of the construction machinery equipment in the user-submitted order demand is checked to see if it is less than the difference between the order submission time and the estimated arrival time. Second, the existence of at least one optimal warehouse within a preset range is determined based on the delivery address information in the user-submitted order demand. Third, the maximum daily automatic scheduling volume of the optimal warehouse is checked to see if it is greater than 0. When all of the above processes are satisfied, the order demand is determined to be a target order demand that meets the conditions for full management.

[0042] Furthermore, target order demands are filtered from several orders for construction machinery and equipment, and these target orders can be used for intelligent scheduling. However, because construction machinery and equipment leasing actually faces various complex situations, some orders require manual scheduling based on human experience. That is, the remaining order demands that do not meet the preset conditions for full management require manual scheduling. For example, during equipment use, unexpected equipment failures, changes in customer needs, or discrepancies between the actual conditions at the construction site and expectations may occur. These situations often exceed the prediction range of the automated scheduling system and require manual handling. Experienced dispatchers can flexibly adjust equipment allocation and scheduling strategies according to the specific circumstances.

[0043] The warehouse allocation module 102 is used to calculate the corresponding shipping warehouse information for several target order requirements by combining the warehouse allocation algorithm with the warehouse information of engineering machinery and equipment, and to generate the corresponding outbound information.

[0044] In one embodiment, the process of calculating the corresponding shipping warehouse information for several target order demands using a warehouse allocation algorithm includes: calculating the actual driving path distance between the target order demand and each warehouse in the construction machinery equipment warehouse information based on the receiving address information in the target order demand; sorting the actual driving path distances in ascending order, and selecting several warehouses that meet the preset nearest principle based on the sorting results; and matching the equipment list information corresponding to the several warehouses with the target order demand to obtain the shipping warehouse information and outbound information corresponding to the target order demand.

[0045] In this embodiment, the equipment list information is primarily represented using SKU (Stock Keeping Unit) codes. SKU coding is a unique numbering system used to identify and manage goods. Each SKU code represents a specific product or product variant and typically includes key product characteristics such as model number, size, color, and packaging information. Through SKU coding, enterprises can efficiently track inventory, manage the supply chain, and conduct sales analysis, helping to improve the efficiency and accuracy of inventory management. SKU coding is widely used in retail, logistics, warehousing, and e-commerce, providing crucial support for optimizing inventory management and improving operational efficiency.

[0046] It should be noted that multiple target order demands are selected and warehouse allocation calculations are performed simultaneously. The warehouse allocation algorithm in this application supports parallel computing, meaning that several target order demands can be independently input into the warehouse allocation algorithm, and each will obtain its own calculation results, which greatly reduces the overall computing time and can significantly improve efficiency, especially when processing large amounts of data.

[0047] For example, taking a single target order request as an example, firstly, using the delivery address information of the target order request as the center, the actual driving distance of all warehouses from the delivery address information is calculated; then, the actual driving distances are sorted in ascending order, and the top five warehouses are selected according to a preset nearest principle. Each warehouse contains a set of SKU codes for all construction machinery equipment stored in that warehouse; the equipment parameter information of the target order request is matched with all SKU codes in the five warehouses to find the corresponding warehouse where the SKU code matches the equipment parameter information of the target order request; if there are two warehouses that match the equipment parameter information of the target order request, the warehouse closest to the delivery address of the target order request is selected as the shipping warehouse information; the SKU code in that warehouse that matches the equipment parameter information of the target order request is used as the outbound information.

[0048] Furthermore, when submitting a target order request, users need to choose whether to allow device model substitution. If "Allow Model Substitution" is selected, one or more alternative device types will be provided for each device type when submitting the required equipment, and priority levels will be set among the alternative device types. For example, when matching the SKU code of the device type in the current target order request, if no matching SKU code is found, SKU code matching can be performed based on the alternative device types of the current target order request. Among the multiple alternative device types, SKU code matching will be performed sequentially according to the priority level of the alternative device types. If no matching SKU code is found for the device type in the current target order request or for the multiple alternative device types, the system will transfer the order to manual processing. If "Do Not Allow Model Substitution" is selected, only one specific device type solution needs to be submitted when submitting the target order request. If the solution cannot be matched, the system will transfer the target order request to manual processing, ensuring the accuracy and timeliness of order processing and meeting the personalized needs of users.

[0049] The loading module 103 is used to generate shipping and transportation scheduling information based on the shipping warehouse information and outbound information corresponding to each target order demand using a loading algorithm, and to generate return and transportation scheduling information based on the return and shipping warehouse information within each target order demand using a loading algorithm.

[0050] It should be noted that the transportation process for the engineering machinery equipment required by the target order is divided into two parts: outbound transportation and return transportation. When a target order is submitted, the loading module 103 performs outbound transportation scheduling, that is, transporting the equipment from the warehouse to the address recorded in the receiving address information. When only a single target order is submitted, the transportation method is one-to-one loading and unloading, that is, the equipment is directly transported from the warehouse to the address recorded in the receiving address information. When multiple target orders are submitted, the transportation method is one-to-many loading and unloading, that is, the transportation of construction machinery equipment with multiple target orders is carried out by one transport vehicle to different addresses recorded in the receiving address information. When the construction machinery equipment is no longer in use, the loading module 103 performs return transportation scheduling. When only a single target order is submitted, the transportation method is one-to-one loading and unloading, that is, the equipment is directly transported from the address recorded in the receiving address information to the outbound warehouse. When multiple target orders are submitted, the transportation method is multiple-to-one loading and unloading, that is, the transportation of construction machinery equipment with multiple target orders is carried out by one transport vehicle to different addresses recorded in the receiving address information to be loaded and sent to the same original warehouse.

[0051] Furthermore, to accommodate unforeseen events that may occur during the rental of engineering equipment, such as user requests to extend or shorten usage time, sudden equipment failures, or the need to change the delivery address, the outbound and return transportation scheduling in this embodiment is executed in real-time and does not require advance planning. The delivery address information and the end-of-use time of the engineering machinery equipment in the target order requirements can be adjusted according to actual needs and are not fixed.

[0052] In one embodiment, the shipment transportation scheduling information is generated using a loading algorithm based on the shipping warehouse information and outbound information corresponding to each target order demand. The specific process includes: calculating several shipment vehicle loading information based on the shipping warehouse information and outbound information of several target order demands using a loading algorithm; the shipment vehicle loading information includes: shipment vehicle consolidation mode, delivery route planning, and shipment transportation cost; filtering based on the corresponding transportation costs among the several vehicle loading information to select shipment vehicle loading information that meets preset cost requirements; and using the shipment vehicle consolidation mode and delivery route planning of the vehicle loading information that meets the preset cost requirements as the shipment transportation scheduling information.

[0053] The loading algorithm involves the interaction and simultaneous calculation of delivery route planning and vehicle consolidation mode. The calculation methods used include genetic algorithms, simulated annealing, ant colony optimization, particle swarm optimization, etc. This embodiment does not limit the methods and can be selected according to the actual situation.

[0054] In this embodiment, when only one target order demand is submitted to the loading algorithm within the same time period, the loading module will directly allocate the corresponding vehicle according to the target order demand and select the shortest direct route for loading, generating shipment transportation scheduling information. If there are two or more target order demands within the same time period, the loading module will first use the loading algorithm to generate multiple shipment vehicle loading information schemes based on multiple target order demands; then, based on the cost requirements of the engineering machinery equipment types in the multiple shipment vehicle loading information schemes, it will filter out several shipment vehicle loading information schemes whose cost requirements for each engineering machinery equipment type meet preset conditions; finally, it will determine the optimal loading scheme by selecting the vehicle loading information scheme with the lowest shipment transportation cost among the several shipment vehicle loading information schemes that meet the preset cost requirements, and generate shipment transportation scheduling information. This method, through flexible loading algorithms and route planning strategies, can automatically adjust the processing method according to the number of orders and actual needs, thereby improving loading efficiency and the optimization of transportation routes.

[0055] It should be noted that different types of construction machinery have different cost requirements, and the total cost requirements for different vehicle loading schemes will also differ. For example, the cost requirement for a scissor lift is: cost savings - 30 × number of overloaded cargo points, and the cost requirement for a boom lift is: cost savings - 12 × number of overloaded equipment, etc. The cost requirements for each type of construction machinery are preferably greater than 0, provided that the preset condition is met. Cost savings are the difference between the single-vehicle loading requirement for a single target order and the transportation cost of the grouped loading calculated by the loading algorithm. The number of overloaded cargo points refers to the number of construction machinery equipment to be assembled, and the number of overloaded equipment refers to the number of construction machinery equipment exceeding the preset benchmark standard.

[0056] Preferably, in order to improve transportation efficiency and reduce transportation costs, it is further restricted that in the loading of multiple target order demands, a single target order demand is not allowed to be split into multiple vehicles for transportation. If multiple vehicles are assigned to the same target order demand at the same time, the multiple loading and unloading and coordination between different vehicles may increase waiting time and transfer process, thus affecting transportation efficiency.

[0057] In one embodiment, the process of generating exit transportation scheduling information based on exit information and shipping warehouse information within each target order demand using a loading algorithm includes: calculating several exit vehicle loading information based on exit information and shipping warehouse information of several target order demands using a loading algorithm; the exit vehicle loading information includes: exit vehicle consolidation mode, exit route planning, and exit transportation cost; filtering based on the corresponding transportation costs among the several vehicle loading information to select exit vehicle loading information that meets preset cost requirements, and using the exit vehicle consolidation mode and exit route planning of the vehicle loading information that meets the preset cost requirements as exit transportation scheduling information.

[0058] The loading algorithm involves mutual influence between the exit route planning and the cargo consolidation mode of exit vehicles, which usually need to be calculated simultaneously. The calculation methods include genetic algorithms, simulated annealing, ant colony optimization, particle swarm optimization, etc. This embodiment does not limit the methods and the appropriate method can be selected according to the actual situation.

[0059] In this embodiment, as Figure 3As shown, when only one target order demand is submitted to the loading algorithm within the same time period, the loading module will directly allocate the corresponding vehicle according to the target order demand and select the shortest direct route for loading, generating exit transportation scheduling information. If there are two or more target order demands within the same time period, the loading module will first use the loading algorithm to generate multiple exit vehicle loading information schemes based on multiple target order demands; then, based on the cost requirements of the engineering machinery equipment types in the multiple exit vehicle loading information schemes, it will filter out several exit vehicle loading information schemes whose cost requirements for each engineering machinery equipment type meet preset conditions; finally, it will determine the optimal loading scheme by selecting the vehicle loading information scheme with the lowest exit transportation cost among the several exit vehicle loading information schemes that meet the preset cost requirements, and generate exit transportation scheduling information. This method, through flexible loading algorithms and route planning strategies, can automatically adjust the processing method according to the number of orders and actual needs, thereby improving loading efficiency and the optimization of transportation routes.

[0060] It should be noted that different types of construction machinery have different cost requirements, and the corresponding total cost requirements for different vehicle loading schemes also differ. For example, the cost requirement for a scissor lift is: cost savings - 30 × number of overloaded cargo points, and the cost requirement for a boom lift is: cost savings - 120 × number of overloaded equipment, etc. The cost requirements for each type of construction machinery are preferably greater than 0, provided that the preset condition is met. Cost savings are the difference between the single-vehicle loading requirement for a single target order and the transportation cost of the grouped loading calculated by the loading algorithm. The number of overloaded cargo points refers to the number of construction machinery equipment to be assembled, and the number of overloaded equipment refers to the number of construction machinery equipment exceeding the preset benchmark standard.

[0061] In one embodiment, the process of generating exit transportation scheduling information based on exit information and shipping warehouse information within each target order demand using a loading algorithm includes: matching the exit time in the exit information of the current target order demand with the current time; if the exit time and the current time are successfully matched, generating exit transportation scheduling information for the current target order demand based on the exit time and shipping warehouse information.

[0062] In this embodiment, when a target order demand is submitted to the loading algorithm, the system records the return information of the current target order demand, which includes the arrival time and the departure time. After the loading algorithm calculates the shipment transportation scheduling information for the current target order demand, if the departure time in the departure information of the target order demand is the same as the current time, the system will automatically input the target order demand into the loading algorithm to generate departure transportation scheduling information. This method, by submitting the target fixed-point demand once and automatically calculating the departure information through loading, reduces the repeated submission of target order shipments and departures, significantly improving the system's operating efficiency.

[0063] The transportation execution module 104 is used to send transportation execution instructions to the logistics transportation system based on outbound transportation scheduling information or return transportation scheduling information, so as to arrange vehicles to transport engineering machinery and equipment.

[0064] Specifically, such as Figure 4 As shown, when the transportation execution module 104 receives outbound transportation scheduling information or return transportation scheduling information, the transportation execution module 104 issues picking task work orders and outbound task work orders to the warehouse and logistics demand orders to the logistics system based on the outbound transportation scheduling information or return transportation scheduling information. After receiving the logistics demand order, the logistics system arranges vehicles to perform outbound transportation scheduling or return transportation scheduling.

[0065] In addition, the transportation execution module also has a task monitoring function, which can track the transportation status of each vehicle in real time, including its current location and estimated arrival time, to ensure that each transportation task is completed within the scheduled time.

[0066] like Figure 5 The diagram illustrates an intelligent scheduling method for construction machinery equipment rental according to an embodiment of the present invention, applied to the intelligent scheduling system for construction machinery equipment rental as described above; the specific steps are as follows:

[0067] Step S51: Filter several order requirements for construction machinery and equipment based on the fully managed model to obtain several target order requirements that meet the preset fully managed conditions.

[0068] Step S52: For several target order requirements, the corresponding shipping warehouse information is calculated by combining the warehouse information of engineering machinery and equipment warehouses, and the corresponding outbound information is generated.

[0069] Step S53: Based on the shipping warehouse information and outbound information corresponding to each target order demand, use the loading algorithm to generate shipping transportation scheduling information, and based on the return information and shipping warehouse information within each target order demand, use the loading algorithm to generate return transportation scheduling information.

[0070] Step S54: Send a transportation execution instruction to the logistics transportation system based on the outbound transportation scheduling information or the return transportation scheduling information to arrange vehicles to transport engineering machinery and equipment.

[0071] It should be understood that the specific process of performing the above-mentioned steps has been described in detail in the above system embodiments, and will not be repeated here for the sake of brevity.

[0072] It should also be understood that the module division in the embodiments of this application is illustrative and only represents a logical functional division; in actual implementation, there may be other division methods. Furthermore, the functional modules in the various embodiments of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0073] Figure 6 This is a schematic block diagram of the electronic terminal provided in an embodiment of this application. Figure 6 As shown, the electronic terminal includes at least one processor 601, a memory 602, at least one network interface 603, and a user interface 605. The various components in the device are coupled together via a bus system 604. It is understood that the bus system 604 is used to implement communication between these components. In addition to a data bus, the bus system 604 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in… Figure 6 The general will label all buses as bus systems.

[0074] The user interface 605 may include a monitor, keyboard, mouse, trackball, clicker, button, touchpad, or touch screen.

[0075] It is understood that memory 602 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM) or programmable read-only memory (PROM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable categories of memory.

[0076] In this embodiment of the invention, the memory 602 is used to store various types of data to support the operation of the electronic terminal 600. Examples of this data include: any executable program for operation on the electronic terminal 600, such as the operating system 6021 and application program 6022; the operating system 6021 contains various system programs, such as the framework layer, core library layer, driver layer, etc., for implementing various basic services and handling hardware-based tasks. The application program 6022 may contain various applications, such as media players, browsers, etc., for implementing various application services. The intelligent scheduling method for engineering machinery equipment leasing provided in this embodiment of the invention can be included in the application program 6022.

[0077] The methods disclosed in the above embodiments of the present invention can be applied to processor 601, or implemented by processor 601. Processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 601 or by instructions in the form of software. The processor 601 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 601 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. General-purpose processor 601 may be a microprocessor or any conventional processor, etc. The steps of the accessory optimization method provided in the embodiments of the present invention can be directly reflected as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in a memory. The processor reads the information in the memory and combines it with its hardware to complete the steps of the aforementioned method.

[0078] In an exemplary embodiment, the electronic terminal 600 may be used to execute the aforementioned method by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs).

[0079] According to the method provided in the embodiments of this application, this application also provides a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to execute the intelligent scheduling method for engineering machinery equipment leasing in any of the embodiments shown.

[0080] According to the method provided in the embodiments of this application, this application also provides a computer-readable storage medium storing program code, which, when run on a computer, causes the computer to execute the intelligent scheduling method for engineering machinery equipment leasing in any of the embodiments shown.

[0081] As used in this specification, the terms "component," "module," "system," etc., are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. As illustrated, applications running on computing devices and computing devices can both be components. One or more components may reside in a process and / or an execution thread, and components may be located on a single computer and / or distributed among two or more computers. Furthermore, these components can be executed from various computer-readable media on which various data structures are stored. Components can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, and / or a network, such as the Internet interacting with other systems via signals).

[0082] Those skilled in the art will recognize that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0083] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0085] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0086] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0087] In the above embodiments, the functions of each functional unit can be implemented entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. A computer program product includes one or more computer instructions (programs). When the computer program instructions (programs) are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs, DVDs), or semiconductor media (e.g., solid-state disks, SSDs, etc.).

[0088] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0089] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0090] In summary, this application provides an intelligent scheduling system, method, medium, program product, and terminal for engineering machinery and equipment leasing. The application constructs an intelligent scheduling system comprising an order screening module, a warehouse allocation module, a vehicle allocation module, and an execution module. It achieves the coordinated operation of fully managed algorithms, warehouse allocation algorithms, and vehicle allocation algorithms, automatically filtering and executing processes such as order screening, warehouse selection, vehicle selection, and task assignment in the leasing equipment scheduling process. This not only significantly improves the execution efficiency of the scheduling system but also matches the most suitable warehouse and vehicle for the current order through warehouse allocation and vehicle allocation algorithms, saving time and financial costs and effectively reducing manpower to meet the needs of actual scheduling scenarios. Therefore, this application effectively overcomes the various shortcomings of existing technologies and has high industrial application value.

[0091] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. An intelligent scheduling system for renting construction equipment, characterized in that, The application relates to a complete management model for an order screening module, a warehouse allocation module, a loading allocation module and a transportation execution module. The order screening module is used for screening a plurality of order demands for engineering machinery equipment based on a complete management model to obtain a plurality of target order demands meeting preset complete management conditions. The warehouse allocation module is used for calculating corresponding delivery warehouse information and generating corresponding delivery information by using a warehouse allocation algorithm in combination with engineering machinery equipment warehouse information for the plurality of target order demands. The loading allocation module is used for generating delivery transportation scheduling information by using a loading allocation algorithm based on the delivery warehouse information and the delivery information corresponding to each target order demand, and generating off-site transportation scheduling information by using a loading allocation algorithm based on off-site information and delivery warehouse information in each target order demand. The transportation execution module is used for sending transportation execution instructions to a logistics transportation system according to the delivery transportation scheduling information or the off-site transportation scheduling information to arrange vehicle transportation of engineering machinery equipment. The process of screening a plurality of order demands for engineering machinery equipment based on a complete management model to obtain a plurality of target order demands meeting preset complete management conditions comprises the following steps.

2. The engineered mechanical equipment rental intelligent dispatch system of claim 1, wherein, Preset complete management conditions are configured in the complete management model; the preset complete management conditions comprise a difference between a predicted arrival time and an approval passing time, a distance between an optimal warehouse and a delivery site, optimal warehouse storage meeting forms, a maximum single quantity of an optimal warehouse accumulated automatic scheduling on a day, and an optimal vehicle. The plurality of order demands for engineering machinery equipment are input into the complete management model for matching; if a current order demand meets the preset complete management conditions, the current order demand is a target order demand meeting the preset complete management conditions. The process of calculating corresponding delivery warehouse information for the plurality of target order demands by using a warehouse allocation algorithm comprises the following steps.

3. The engineered mechanical equipment rental intelligent dispatch system of claim 1, wherein, Actual driving path distances of each warehouse in the target order demand and the engineering machinery equipment warehouse information are calculated based on the delivery address information in the target order demand and the engineering machinery equipment warehouse information to obtain the actual driving path distances. The actual driving path distances are sorted in ascending order, and a plurality of warehouses meeting a preset nearest principle are screened based on the sorting result. The target order demand corresponding delivery warehouse information and delivery information are obtained by matching the device list information corresponding to the plurality of warehouses and the target order demand. The process of generating delivery transportation scheduling information based on the delivery warehouse information and the delivery information corresponding to each target order demand comprises the following steps.

4. The intelligent dispatching system for rental of construction equipment as claimed in claim 1 wherein, Delivery vehicle loading information is calculated by using a loading allocation algorithm based on the delivery warehouse information and the delivery information of the plurality of target order demands; the delivery vehicle loading information comprises a delivery vehicle mixed delivery mode, a delivery path planning and a delivery transportation cost. The delivery vehicle mixed delivery mode and the delivery path planning of the vehicle loading information meeting the preset cost demand are taken as the delivery transportation scheduling information by screening the transportation cost corresponding to the plurality of vehicle loading information to screen the delivery vehicle loading information meeting the preset cost demand. ​ 5. The intelligent dispatching system for rental of construction equipment as claimed in claim 1 wherein, The return transport scheduling information is generated based on the return information and the delivery warehouse information in each target order demand by using a loading algorithm, and the specific process includes: Based on the return information and the delivery warehouse information of a plurality of target order demands, a plurality of return vehicle loading information is obtained by using a loading algorithm; the return vehicle loading information includes a return vehicle consolidation mode, a return path planning, and a return transport cost; Based on the corresponding transport costs in the plurality of vehicle loading information, return vehicle loading information that meets the preset cost requirement is filtered out, and the return vehicle consolidation mode and the return path planning of the return vehicle loading information that meets the preset cost requirement are used as the return transport scheduling information.

6. The engineered mechanical equipment rental intelligent dispatch system of claim 1, wherein, The process of generating the return transport scheduling information based on the return information and the delivery warehouse information in each target order demand includes: matching the return time in the return information of the current target order demand with the current time, and if the matching is successful, generating the return transport scheduling information of the current target order demand according to the return time and the delivery warehouse information.

7. An intelligent scheduling method for construction equipment rental, characterized by, The method is applied to the engineering machinery equipment rental intelligent scheduling system of any one of claims 1 to 6, and the method includes: A plurality of order demands for engineering machinery equipment are filtered based on a full management model to obtain a plurality of target order demands that meet a preset full management condition; Corresponding delivery warehouse information is obtained by using a warehouse allocation algorithm in combination with engineering machinery equipment warehouse information for a plurality of target order demands, and corresponding delivery information is generated; Based on the corresponding delivery warehouse information and the delivery information of each target order demand, out-delivery transport scheduling information is generated by using a loading algorithm, and return transport scheduling information is generated based on the return information and the delivery warehouse information in each target order demand by using a loading algorithm; Transport execution instructions are sent to a logistics transport system according to the out-delivery transport scheduling information or the return transport scheduling information to arrange vehicle transport of engineering machinery equipment.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the engineering machinery equipment rental intelligent scheduling method of claim 7.

9. A computer program product, characterised in that, The computer program product includes computer program code, and when the computer program code is run on a computer, the computer implements the engineering machinery equipment rental intelligent scheduling method of claim 7.

10. An electronic terminal comprising a memory, a processor and a computer program stored on the memory, characterized in that, The processor executes the computer program to implement the engineering machinery equipment rental intelligent scheduling method of claim 7.

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