Logistics management and control method, apparatus and device, and storage medium

Abstract

The invention discloses a logistics management and control method, device and equipment and a storage medium, and relates to the technical field of logistics management, and the method comprises the steps: obtaining logistics order information; inputting the logistics order information to a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information; determining a target distribution path based on the target logistics cycle information and the target logistics cost information; and carrying out logistics order distribution based on the target distribution path so as to realize management and control of a logistics period and logistics cost. The logistics cycle and the logistics cost can be managed and controlled at the same time, the logistics efficiency is effectively improved, and meanwhile the logistics cost is saved.

Description

Technical Field

[0001] The present application relates to the technical field of equipment performance testing, and in particular to logistics control methods, devices, equipment and storage media. Background Art

[0002] In modern supply chain management, logistics management is crucial to the efficiency and cost control of enterprise operations. With the acceleration of the globalization process, market demand is becoming increasingly diversified and changing rapidly, and traditional logistics models are facing many challenges. The existing logistics model usually has the following two significant problems: 1. Long logistics cycle. Traditional logistics transportation methods are often subject to external factors such as transportation methods, road conditions, weather, etc., and usually have relatively fixed transportation routes and transportation times. Especially in the cross-border and cross-regional logistics process, the logistics cycle is often long, resulting in the delivery time of goods cannot meet the immediate needs of customers, affecting the market competitiveness and customer satisfaction of enterprises. In addition, long-cycle logistics also increases the risk of inventory backlogs, further pushing up operating costs. 2. High logistics costs. Due to the increasing market requirements for logistics speed and service quality, many companies have chosen high-cost logistics solutions, such as air transportation and fast transportation. However, although these efficient transportation methods can shorten the logistics cycle, they are accompanied by higher transportation costs. At the same time, some traditional logistics networks will also increase transportation costs due to inefficient scheduling and non-optimized transportation routes, further increasing the operating pressure of enterprises.

[0003] Due to the above problems, enterprises often face the dilemma of "speed and cost" in logistics management: if the priority is to shorten the logistics cycle, it often requires a higher cost; if the priority is to control the logistics cost, the logistics cycle will inevitably be extended. Therefore, how to achieve effective control of logistics cycle and cost while ensuring the quality of logistics services has become a major problem in current logistics management.

[0004] Therefore, how to simultaneously control the logistics cycle and logistics costs, effectively improve logistics efficiency, and save logistics costs is a problem that urgently needs to be solved.

[0005] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0006] The main purpose of this application is to provide a logistics management method, device, equipment and storage medium, aiming to solve the technical problem that it is impossible to control the logistics cycle and logistics costs at the same time.

[0007] To achieve the above objectives, the present application proposes a logistics control method, which includes:

[0008] Get logistics order information;

[0009] Inputting the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information;

[0010] Determine a target delivery route based on the target logistics cycle information and the target logistics cost information;

[0011] Logistics orders are delivered based on the target delivery path to achieve management and control of logistics cycle and logistics costs.

[0012] In one embodiment, the inputting the logistics order information into the logistics cycle model and the logistics cost model to obtain the target logistics cycle information and the target logistics cost information includes:

[0013] Determine the shipping address, receiving address, cargo weight, cargo volume, and cargo type based on the logistics order information;

[0014] Determine the mode of transportation according to the weight of the goods, the volume of the goods and the type of the goods;

[0015] According to the shipping address, the receiving address and the transportation method, a logistics cycle model is used to predict and obtain target logistics cycle information of each logistics order;

[0016] The target logistics cost information of each logistics order is obtained by predicting the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method through the logistics cost model.

[0017] In one embodiment, the prediction is performed using a logistics cycle model according to the shipping address, the receiving address, and the transportation method to obtain target logistics cycle information of each logistics order, including:

[0018] Obtain the order shipment time, and predict the shipment time, unloading completion time, channel warehousing time, channel shipment time, and customer delivery receipt time based on the order shipment time, shipping address, delivery address, and transportation method;

[0019] Determine the factory delivery cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle of each logistics order according to the order delivery time, the predicted delivery time, the unloading completion time, the channel warehousing time, the channel delivery time and the customer delivery receipt time;

[0020] The target logistics cycle information of each logistics order is obtained by predicting the delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order through the logistics cycle model.

[0021] In one embodiment, the logistics cycle model is:

[0022]

[0023] Among them, T total is the target logistics cycle information predicted by the logistics cycle model, T prod is the factory cycle, T transit is the transit period, T shorthaul is the short-haul cycle, T storage is the storage cycle, T dislivery is the distribution cycle, ω1, ω2, ω3, ω4, ω5 are the weights of the factory cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle respectively, γ is the interaction effect between the in-transit cycle and the short-haul cycle, T prod (t-1) is the factory cycle at the previous moment, δ is the hysteresis coefficient, E is the environmental factor, and θ is the adjustment coefficient.

[0024] In one embodiment, the prediction is performed using a logistics cost model based on the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type, and the transportation method to obtain target logistics cost information for each logistics order, including:

[0025] Determine the transportation fee, storage fee, packaging fee and insurance fee according to the shipping address, the receiving address, the weight of the goods, the volume of the goods, the type of goods and the mode of transportation;

[0026] The transportation costs, storage costs, packaging costs and insurance costs are predicted through a logistics cost model to obtain target logistics cost information for each logistics order.

[0027] In one embodiment, the logistics cost model is:

[0028]

[0029] Among them, C total The target logistics cost information predicted by the logistics cost model, is the transportation cost of the i-th logistics order, is the storage fee of the i-th logistics order, is the packaging cost of the i-th logistics order, is the insurance cost of the i-th logistics order, α0 is the basic logistics cost, α1, α2, α3, α4 are the impact coefficients of transportation cost, warehousing cost, packaging cost and insurance cost respectively, X i is the characteristic vector of the i-th logistics order, β is X iThe coefficient vector composed of the coefficients of each feature in , λ1 is the timeliness factor of the i-th logistics order The coefficient of λ2 is the seasonal factor of the i-th logistics order. The coefficient of σ is the customer historical cost of the i-th logistics order is the coefficient of the feature interaction term, indicating that feature X ij and X ik The interaction between them.

[0030] In one embodiment, determining the target delivery path based on the target logistics cycle information and the target logistics cost information includes:

[0031] Determining the delivery priority of each logistics order based on the target logistics cycle information and the target logistics cost information;

[0032] Performing route planning according to the delivery priority of each logistics order and the corresponding delivery address to obtain multiple delivery routes;

[0033] Iteratively optimize each of the distribution paths, with the goal of minimizing the total logistics cost and the total logistics cycle, and select the target distribution path.

[0034] In addition, to achieve the above objectives, the present application also proposes a logistics control device, which includes:

[0035] Acquisition module, used to obtain logistics order information;

[0036] An input module, used to input the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information;

[0037] A determination module, configured to determine a target delivery path based on the target logistics cycle information and the target logistics cost information;

[0038] The distribution module is used to distribute logistics orders based on the target distribution path to achieve the management and control of logistics cycle and logistics cost.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a logistics control device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the logistics control method described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the logistics control method described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the logistics control method described above.

[0042] One or more technical solutions proposed in the present application obtain logistics order information; input the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information; determine a target delivery path based on the target logistics cycle information and the target logistics cost information; and deliver logistics orders based on the target delivery path to achieve management and control of logistics cycles and logistics costs. The logistics cycles and logistics costs can be managed and controlled at the same time, effectively improving logistics efficiency and saving logistics costs.

[0043] In summary, the present application uses a logistics cycle model and a logistics cost model to quickly and accurately predict target logistics cycle information and target logistics cost information based on logistics order information, and then determines the target delivery route and performs logistics order delivery based on the target logistics cycle information and the target logistics cost information, thereby realizing the management and control of logistics cycle and logistics cost, overcoming the technical defect of being unable to manage logistics cycle and logistics cost at the same time, and being able to manage logistics cycle and logistics cost at the same time, effectively improving logistics efficiency, and saving logistics costs at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1 A flow chart of the first embodiment of the logistics control method of this application;

[0047] Figure 2 A flow chart of the second embodiment of the logistics control method of this application;

[0048] Figure 3 This is a schematic diagram of the module structure of the logistics control device of the embodiment of the present application;

[0049] Figure 4 Schematic diagram of the equipment structure of the hardware operating environment involved in the logistics control method in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] The main solution of the embodiment of the present application is: obtain logistics order information; input the logistics order information into the logistics cycle model and the logistics cost model to obtain target logistics cycle information and target logistics cost information; determine the target delivery path based on the target logistics cycle information and the target logistics cost information; and perform logistics order delivery based on the target delivery path to achieve management and control of logistics cycle and logistics cost.

[0054] Enterprises often face the dilemma of "speed and cost" in logistics management: if the priority is to shorten the logistics cycle, it often requires a higher cost; if the priority is to control the logistics cost, the logistics cycle will inevitably be extended. Therefore, how to achieve effective control of logistics cycle and cost while ensuring the quality of logistics services has become a major problem in current logistics management. Therefore, how to control the logistics cycle and logistics cost at the same time, effectively improve logistics efficiency, and save logistics costs is a problem that needs to be solved urgently.

[0055] The present application uses a logistics cycle model and a logistics cost model to quickly and accurately predict target logistics cycle information and target logistics cost information based on logistics order information, and then determines the target delivery route and performs logistics order delivery based on the target logistics cycle information and target logistics cost information, thereby realizing the management and control of logistics cycle and logistics cost, overcoming the technical defect of being unable to manage logistics cycle and logistics cost at the same time, and being able to manage logistics cycle and logistics cost at the same time, effectively improving logistics efficiency, and saving logistics costs at the same time.

[0056] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a logistics control device, etc. The following takes the logistics control device as an example to illustrate this embodiment and the following embodiments.

[0057] Based on this, the present application embodiment provides a logistics management method, referring to Figure 1 , Figure 1This is a flow chart of the first embodiment of the logistics control method of the present application.

[0058] In this embodiment, the logistics management method includes steps S10 to S40:

[0059] Step S10: Obtain logistics order information.

[0060] It should be noted that logistics order information can come from a variety of channels, such as orders submitted directly by customers, order data provided by partners, or order information automatically collected by logistics management software. This embodiment does not impose specific restrictions on this.

[0061] It is understandable that the order information includes at least the order number, shipping address, receiving address, cargo weight, cargo volume, cargo type, and delivery time requirements, and this embodiment does not impose specific restrictions on this.

[0062] Specifically, in order to ensure the accuracy of information, after obtaining the logistics order information, it is necessary to check and verify the information, because any error in the order information may lead to the failure or inefficiency of logistics distribution. Checking and verifying can be done by confirming information with customers, using the verification function of logistics management software, or performing data matching and error detection through automated systems.

[0063] Step S20: input the logistics order information into the logistics cycle model and the logistics cost model to obtain the target logistics cycle information and the target logistics cost information.

[0064] It should be noted that the logistics cycle model and logistics cost model will analyze the acquired logistics order information. The logistics cycle model will predict the time required for the entire logistics cycle, while the logistics cost model will estimate the total cost required to complete the distribution. The logistics cycle model and logistics cost model can be statistical models based on historical data or prediction models trained using machine learning algorithms to improve the accuracy and efficiency of predictions.

[0065] It is understood that the logistics cycle model and the logistics cost model will be calculated based on the input order information. The logistics cycle model will consider factors such as the type, weight, volume, and delivery time requirements of the goods to predict the time required to complete the entire logistics cycle. The logistics cost model will calculate the total cost required to complete the delivery based on parameters such as the weight, volume, transportation distance, and transportation method of the goods, which is not specifically limited in this embodiment.

[0066] It is worth noting that the construction of logistics cycle models and logistics cost models can adopt a variety of technical means, such as linear regression, time series analysis, neural network and other methods to build models. These models can learn the relationship between logistics cycle and cost based on historical data and predict the logistics cycle and cost of future orders. In addition, the model can also be dynamically adjusted according to real-time data to adapt to changes in market and operating conditions.

[0067] In the specific implementation, after the logistics cycle model and logistics cost model are initially constructed, they need to be trained to ensure that the model's prediction results have high accuracy and reliability. The training process usually includes inputting a large amount of historical logistics order data, which covers information such as different cargo types, weights, volumes, and delivery time requirements, as well as corresponding logistics cycle and cost data. Through this data, the model can learn and identify the complex relationship between logistics cycle and cost, thereby improving the accuracy of the prediction.

[0068] It is worth noting that the logistics cycle model and logistics cost model are constantly optimized during use to adapt to the new logistics environment and market changes. The optimization process may include collecting new logistics order data, analyzing the changing trends of logistics cycles and costs, and adjusting model parameters to improve the accuracy of predictions. The logistics cycle model and logistics cost model can also be dynamically adjusted based on real-time data to adapt to changes in market and operating conditions. In the model optimization process, supervised learning and unsupervised learning methods in machine learning can be used. By continuously learning new logistics data, the model can self-adjust and optimize to maintain the accuracy of the prediction. For example, when using supervised learning methods, the model is trained based on historical data with correct answers, while unsupervised learning allows the model to find patterns and structures in unlabeled data. Through these methods, the logistics cycle model and logistics cost model can continue to improve and adapt to the changing logistics environment.

[0069] Model optimization is an ongoing process that requires continuous adjustment and improvement based on real-time data to adapt to market and business changes. The construction and optimization of logistics cycle models and logistics cost models can be completed automatically by logistics management and control equipment, or supervised and intervened by professionals.

[0070] Step S30: Determine a target delivery route based on the target logistics cycle information and the target logistics cost information.

[0071] It should be noted that the target delivery path refers to the optimal delivery path that minimizes the total logistics cost and the total logistics cycle. In order to determine the target delivery path, a variety of optimization algorithms can be used, such as genetic algorithms, ant colony algorithms, or simulated annealing algorithms, which can handle complex constraints such as traffic conditions, delivery time windows, and vehicle capacity constraints, so as to find the optimal or approximately optimal delivery solution.

[0072] It is understandable that when determining the target delivery path, factors such as actual geographic information, traffic flow, weather conditions, and the priority of the delivery point are considered. These factors work together to select the delivery path to ensure that the optimal balance between cost and time is achieved while meeting all constraints. For example, the genetic algorithm continuously iterates and optimizes the path selection by simulating the process of natural selection, while the ant colony algorithm imitates the behavior of ants in finding food paths and finds the shortest path through the accumulation and volatilization of pheromones. The simulated annealing algorithm simulates the physical annealing process and allows the system to jump out of the local optimal solution with a certain probability to find the global optimal solution. The selection and application of these algorithms depends on the complexity of the specific problem and the accuracy requirements of the solution. Ultimately, the determination of the target delivery path will provide an efficient and economical solution for logistics distribution, thereby improving the performance of the entire logistics system.

[0073] In a feasible implementation, step S30 includes: determining the delivery priority of each logistics order based on the target logistics cycle information and the target logistics cost information; performing path planning according to the delivery priority of each logistics order and the corresponding delivery address to obtain multiple delivery paths; iteratively optimizing each delivery path to select the target delivery path with the goal of minimizing the total logistics cost and the total logistics cycle.

[0074] It should be noted that the delivery priority of logistics orders is determined based on the predicted target logistics cycle information and target logistics cost information to ensure that under limited resources and time conditions, those orders that have the greatest impact on overall logistics efficiency are given priority.

[0075] It is understandable that in the path planning stage, the delivery priority and delivery address of all logistics orders are comprehensively considered, and multiple feasible delivery paths are calculated through algorithms. These paths will be evaluated and compared to determine which path can minimize the total logistics cost and total logistics cycle while meeting all constraints. The iterative optimization process may involve multiple calculations and comparisons until the optimal solution or the approximate optimal solution that meets the preset conditions is found. The final selected target delivery path will serve as a guiding plan for logistics distribution, guiding logistics vehicles to complete the delivery task in the most economical and efficient way.

[0076] It is worth noting that during the iterative optimization of the distribution path, the distribution order and route on the path are continuously adjusted to achieve the optimal balance between cost and time, thereby ensuring that the efficiency and cost of logistics distribution are within a reasonable range.

[0077] Specifically, the iterative optimization of the distribution path may need to consider real-time traffic information, weather changes, vehicle failures and other emergencies, all of which may have an impact on the distribution path. Therefore, the logistics distribution system needs to have a certain degree of flexibility and adaptability to adapt to these unpredictable events. For example, if a predetermined path becomes unfeasible due to traffic congestion, the system should be able to quickly recalculate and provide an alternative path to ensure the smooth completion of the distribution task. In addition, in order to further improve the distribution efficiency, the logistics distribution system can also integrate advanced communication technologies, such as Internet of Things (IoT) devices, to monitor vehicle location and cargo status in real time, and ensure the transparency and traceability of logistics information. Through these comprehensive measures, the logistics cycle model and logistics cost model can provide more accurate and efficient decision support for logistics distribution.

[0078] Step S40: Perform logistics order delivery based on the target delivery path to achieve management and control of logistics cycle and logistics cost.

[0079] It should be noted that during the logistics order delivery process, the logistics distribution system will continuously track the location and status of the delivery vehicles to ensure that the delivery tasks are carried out according to the target delivery route and schedule. If there are deviations, the system will automatically or manually intervene to make necessary adjustments to ensure that the delivery efficiency and cost are within the target range.

[0080] Understandably, the distribution plan can also be dynamically adjusted based on real-time data, such as traffic conditions and weather changes, to cope with unforeseen delays or changes. In this way, the logistics cycle model and logistics cost model not only play a role in the planning stage before distribution, but also provide continuous support throughout the distribution process to ensure the flexibility and reliability of logistics distribution. Ultimately, through precise logistics cycle and cost control, the logistics distribution system can significantly improve overall logistics efficiency, reduce operating costs, and provide customers with better services.

[0081] The present embodiment provides a logistics management and control method, which obtains logistics order information; inputs the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information; determines a target delivery path based on the target logistics cycle information and the target logistics cost information; and delivers logistics orders based on the target delivery path to achieve management and control of logistics cycles and logistics costs. The logistics cycle and logistics costs can be managed at the same time, effectively improving logistics efficiency and saving logistics costs.

[0082] In summary, this embodiment uses a logistics cycle model and a logistics cost model to quickly and accurately predict target logistics cycle information and target logistics cost information based on logistics order information, and then determines the target delivery path and performs logistics order delivery based on the target logistics cycle information and the target logistics cost information, thereby realizing the management and control of logistics cycle and logistics cost, overcoming the technical defect of being unable to manage logistics cycle and logistics cost at the same time, and being able to manage logistics cycle and logistics cost at the same time, effectively improving logistics efficiency, and saving logistics costs at the same time.

[0083] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S20 includes steps S201 to S203:

[0084] Step S201: Determine the shipping address, receiving address, cargo weight, cargo volume, and cargo type according to the logistics order information.

[0085] It should be noted that the shipping address refers to the starting point of logistics distribution, while the receiving address is the end point of distribution. The weight and volume of goods are important factors affecting the distribution cost and the selection of appropriate transportation tools. The type of goods is related to the special handling or storage conditions that may be required during the distribution process. By accurately obtaining this information, the logistics cycle model and logistics cost model can accurately determine the target logistics cycle information and target logistics cost information of each logistics order, thereby providing scientific decision support for logistics distribution.

[0086] Step S202: Determine the mode of transportation according to the weight of the cargo, the volume of the cargo, and the type of cargo.

[0087] It should be noted that the choice of transportation mode is crucial to the control of logistics costs and cycles. Different cargo characteristics require different transportation modes. For example, for large and light cargo, rail or sea transportation may be more suitable; while for small and heavy cargo, air or road transportation may be preferred. In addition, different types of cargo may also require specific transportation conditions, such as refrigeration, special handling of fragile goods, etc. By comprehensively considering these factors, logistics cycles and costs can be predicted more accurately, thereby optimizing distribution routes and ensuring the best balance between logistics efficiency and cost control.

[0088] Step S203: predicting the target logistics cycle information of each logistics order through a logistics cycle model according to the shipping address, the receiving address and the transportation method.

[0089] It should be noted that when predicting the target logistics cycle information based on the shipping address, receiving address and transportation mode, the logistics cycle model will take into account the timeliness, cost and possible delay risks of various transportation modes. For example, although road transportation is flexible, it may be affected by traffic conditions; and although railway transportation is less expensive, its timeliness may not be as good as air transportation. By analyzing these factors, the logistics cycle model can provide an expected logistics cycle for each order, thereby helping logistics managers make more reasonable distribution plans. In this way, the prediction of logistics cycle and cost is more accurate, and the efficiency and cost control of logistics distribution are also significantly improved.

[0090] In a feasible implementation, step S203 includes: obtaining the order delivery time, and predicting the quasi-shipping time, unloading completion time, channel warehousing time, channel delivery time and customer delivery note time according to the order delivery time, the shipping address, the receiving address and the transportation method; determining the delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order according to the order delivery time, the predicted quasi-shipping time, the unloading completion time, the channel warehousing time, the channel delivery time and the customer delivery note time; predicting the delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order through a logistics cycle model to obtain the target logistics cycle information of each logistics order.

[0091] It should be noted that the on-time dispatch refers to the time when the goods are dispatched from the warehouse, while the unloading completion time refers to the time when the goods arrive at the destination and are unloaded. The channel entry time refers to the time when the goods enter the sales or distribution channel, and the channel exit time refers to the time when the goods are shipped from the channel. The customer receipt time refers to the time when the customer actually receives the goods and confirms it. Through the prediction of these time points, each link in the logistics process can be managed more meticulously to ensure the accuracy and controllability of the logistics cycle.

[0092] It can be understood that the delivery cycle refers to the time from the time the goods leave the warehouse at the production site to the time they start to be transported. The in-transit cycle refers to the time the goods spend in the transportation process, while the short-haul cycle involves the transit time when the goods are converted from one mode of transportation to another. The storage cycle refers to the time the goods are stored in the warehouse, which usually includes the time for warehousing, storage and outbound transportation. Finally, the distribution cycle refers to the entire time span from the shipment of goods from the warehouse to the final delivery to the customer. By accurately calculating these cycles, the logistics cycle model can provide more accurate time management for logistics distribution, thereby improving the efficiency of the entire supply chain.

[0093] It is worth noting that the factory cycle is calculated based on the factory time and the final dispatch time, and the factory cycle = factory time - final dispatch time. The in-transit cycle is calculated based on the unloading completion time and the factory time, and the in-transit cycle = unloading completion time - factory time. The short-haul cycle is calculated based on the channel entry time and the channel exit time, and the short-haul cycle = channel entry time - channel exit time. The storage cycle is calculated based on the channel exit time and the channel entry time, and the storage cycle = channel exit time - channel entry time. The distribution cycle is calculated based on the channel customer receipt time and the channel exit time, and the distribution cycle = channel customer receipt time - channel exit time.

[0094] It is worth noting that the factory cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order are input into the logistics cycle model. The output of the logistics cycle model is the target logistics cycle information of each logistics order. The formula of the logistics cycle model is as follows:

[0095]

[0096] Among them, T total is the target logistics cycle information predicted by the logistics cycle model, T prod is the factory cycle, T transit is the transit period, T shorthaul is the short-haul cycle, T storage is the storage cycle, T dislivery is the distribution cycle, ω1, ω2, ω3, ω4, ω5 are the weights of the factory cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle respectively, γ is the interaction effect between the in-transit cycle and the short-haul cycle, T prod (t-1) is the factory cycle at the previous moment, δ is the hysteresis coefficient, E is the environmental factor, and θ is the adjustment coefficient.

[0097] Step S204: A logistics cost model is used to predict the target logistics cost information of each logistics order based on the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method.

[0098] It should be noted that when predicting the target logistics cost information based on the shipping address, receiving address, cargo weight, cargo volume, cargo type and transportation method, the logistics cost model takes into account a variety of factors, including but not limited to the transportation distance, the volume and weight of the cargo, the efficiency of the transportation method and the type of cargo. These factors together affect the calculation of logistics costs. For example, the longer the transportation distance, the higher the transportation cost; the larger the volume and weight of the cargo, the larger or more transportation may be required, thereby increasing the cost; different modes of transportation (such as air, sea and land transportation) have different cost structures and efficiencies; and different types of cargo may affect the cost of packaging, handling and storage. By integrating these factors, the logistics cost model can predict reasonable logistics costs for logistics service providers and customers, helping them make more informed logistics decisions. In addition, the logistics cost model can also be adjusted based on historical data and market changes to ensure the accuracy and real-time nature of the prediction results.

[0099] In a feasible implementation, step S204 includes: determining the transportation cost, warehousing cost, packaging cost and insurance cost according to the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method; predicting the transportation cost, warehousing cost, packaging cost and insurance cost through a logistics cost model to obtain the target logistics cost information of each logistics order.

[0100] It should be noted that transportation costs refer to the costs incurred during the actual transportation process, which usually include fuel costs, driver wages, vehicle depreciation, etc. Warehousing costs refer to the costs incurred when goods are stored in warehouses, including rent, management fees, insurance premiums, etc. Packaging costs refer to the costs incurred for packaging to protect goods from damage during transportation. Insurance costs refer to the costs incurred for purchasing insurance to reduce accidental losses that may occur during transportation. By incorporating these costs into the logistics cost model, the total cost of logistics orders can be predicted more accurately, providing a basis for cost sharing between logistics service providers and customers.

[0101] It is understood that the shipping cost can be determined by factors such as the weight, volume, mode of transportation, and distance of transportation. The storage cost is calculated based on the volume, weight, and number of days of storage. The packaging cost is determined by the type, volume, weight, and packaging method of the goods. The insurance cost is calculated based on the value of the goods and the transportation risk.

[0102] It is worth noting that the transportation costs, storage costs, packaging costs and insurance costs are input into the logistics cost model. The output of the logistics cost model is the target logistics cost information of each logistics order. The formula of the logistics cost model is as follows:

[0103]

[0104] Among them, C total The target logistics cost information predicted by the logistics cost model, is the transportation cost of the i-th logistics order, is the storage fee of the i-th logistics order, is the packaging cost of the i-th logistics order, is the insurance cost of the i-th logistics order, α0 is the basic logistics cost, α1, α2, α3, α4 are the impact coefficients of transportation cost, warehousing cost, packaging cost and insurance cost respectively, X i is the characteristic vector of the i-th logistics order, β is X i The coefficient vector composed of the coefficients of each feature in , λ1 is the timeliness factor of the i-th logistics order The coefficient of λ2 is the seasonal factor of the i-th logistics order. The coefficient of σ is the customer historical cost of the i-th logistics order is the coefficient of the feature interaction term, indicating that feature X ij and X ik The interaction between them.

[0105] This embodiment accurately evaluates the transportation method to be used based on the cargo weight, cargo volume and cargo type in the logistics order information, and then combines the shipping address, receiving address, cargo weight, cargo volume and cargo type through the logistics cycle model and logistics cost model to accurately and efficiently predict the target logistics cycle information and target logistics cost information of each logistics order.

[0106] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the logistics control method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0107] This application also provides a logistics control device, please refer to Figure 3 , the logistics control device comprises:

[0108] The acquisition module 10 is used to acquire logistics order information.

[0109] The input module 20 is used to input the logistics order information into the logistics cycle model and the logistics cost model to obtain the target logistics cycle information and the target logistics cost information.

[0110] The determination module 30 is used to determine the target delivery route based on the target logistics cycle information and the target logistics cost information.

[0111] The distribution module 40 is used to distribute the logistics orders based on the target distribution path to achieve the management and control of the logistics cycle and logistics costs.

[0112] The logistics control device provided by the present application adopts the logistics control method in the above embodiment, which can solve the technical problem that the logistics cycle and logistics cost cannot be controlled at the same time. Compared with the prior art, the beneficial effects of the logistics control device provided by the present application are the same as the beneficial effects of the logistics control method provided by the above embodiment, and the other technical features in the logistics control device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0113] In one embodiment, the input module 20 is further used to determine the shipping address, receiving address, cargo weight, cargo volume, and cargo type according to the logistics order information;

[0114] Determine the mode of transportation according to the weight of the goods, the volume of the goods and the type of the goods;

[0115] According to the shipping address, the receiving address and the transportation method, a logistics cycle model is used to predict and obtain target logistics cycle information of each logistics order;

[0116] The target logistics cost information of each logistics order is obtained by predicting the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method through the logistics cost model.

[0117] In one embodiment, the input module 20 is further used to obtain the order delivery time, and predict the delivery time, unloading completion time, channel storage time, channel delivery time and customer delivery receipt time according to the order delivery time, the delivery address, the delivery address and the transportation method;

[0118] Determine the factory delivery cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle of each logistics order according to the order delivery time, the predicted delivery time, the unloading completion time, the channel warehousing time, the channel delivery time and the customer delivery receipt time;

[0119] The target logistics cycle information of each logistics order is obtained by predicting the delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order through the logistics cycle model.

[0120] In one embodiment, in the input module 20, the logistics cycle model is:

[0121]

[0122] Among them, T totalis the target logistics cycle information predicted by the logistics cycle model, T pro d is the factory cycle, T transit is the transit period, T shorthaul is the short-haul cycle, T storage is the storage cycle, T dislivery is the distribution cycle, ω1, ω2, ω3, ω4, ω5 are the weights of the factory cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle respectively, γ is the interaction effect between the in-transit cycle and the short-haul cycle, T prod (t-1) is the factory cycle at the previous moment, δ is the hysteresis coefficient, E is the environmental factor, and θ is the adjustment coefficient.

[0123] In one embodiment, the input module 20 is further used to determine the transportation cost, warehousing cost, packaging cost and insurance cost based on the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method; and to predict the transportation cost, warehousing cost, packaging cost and insurance cost through a logistics cost model to obtain the target logistics cost information of each logistics order.

[0124] In one embodiment, in the input module 20, the logistics cost model is:

[0125]

[0126] Among them, C total The target logistics cost information predicted by the logistics cost model, is the transportation cost of the i-th logistics order, is the storage fee of the i-th logistics order, is the packaging cost of the i-th logistics order, is the insurance cost of the i-th logistics order, α0 is the basic logistics cost, α1, α2, α3, α4 are the impact coefficients of transportation cost, warehousing cost, packaging cost and insurance cost respectively, X i is the characteristic vector of the i-th logistics order, β is X i The coefficient vector composed of the coefficients of each feature in , λ1 is the timeliness factor of the i-th logistics order The coefficient of λ2 is the seasonal factor of the i-th logistics order. The coefficient of σ is the customer historical cost of the i-th logistics order is the coefficient of the feature interaction term, indicating that feature X ij and X ik The interaction between them.

[0127] In one embodiment, the determination module is further used to determine the delivery priority of each logistics order based on the target logistics cycle information and the target logistics cost information;

[0128] Performing route planning according to the delivery priority of each logistics order and the corresponding delivery address to obtain multiple delivery routes;

[0129] Iteratively optimize each of the distribution paths, with the goal of minimizing the total logistics cost and the total logistics cycle, and select the target distribution path.

[0130] The present application provides a logistics control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the logistics control method in the above-mentioned embodiment one.

[0131] Reference below Figure 4 , which shows a schematic diagram of the structure of a logistics control device suitable for implementing the embodiment of the present application. The logistics control device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The logistics control equipment shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0132] like Figure 4As shown, the logistics control device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the logistics control device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the logistics control device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a logistics control device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0133] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0134] The logistics control device provided by the present application adopts the logistics control method in the above embodiment, which can solve the technical problem that the logistics cycle and logistics cost cannot be controlled at the same time. Compared with the prior art, the beneficial effects of the logistics control device provided by the present application are the same as the beneficial effects of the logistics control method provided by the above embodiment, and the other technical features in the logistics control device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0135] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0136] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0137] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the logistics management and control method in the above-mentioned embodiment.

[0138] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0139] The above-mentioned computer-readable storage medium may be included in the logistics control device; or it may exist independently without being assembled into the logistics control device.

[0140] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the logistics control device, the logistics control device: obtains logistics order information; inputs the logistics order information into the logistics cycle model and the logistics cost model to obtain target logistics cycle information and target logistics cost information; determines the target delivery path based on the target logistics cycle information and the target logistics cost information; and performs logistics order delivery based on the target delivery path to achieve control of logistics cycle and logistics cost.

[0141] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0142] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0143] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0144] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned logistics control method, and can solve the technical problem that the logistics cycle and logistics costs cannot be controlled at the same time. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the logistics control method provided in the above-mentioned embodiment, and will not be repeated here.

[0145] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned logistics control method when executed by a processor.

[0146] The computer program product provided by this application can solve the technical problem that it is impossible to control the logistics cycle and logistics costs at the same time. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the logistics control method provided by the above embodiment, which will not be repeated here.

[0147] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A logistics control method, characterized in that: The method comprises: Get logistics order information; Inputting the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information; Determine a target delivery route based on the target logistics cycle information and the target logistics cost information; Logistics orders are delivered based on the target delivery path to achieve management and control of logistics cycle and logistics costs.

2. The method according to claim 1, characterized in that The step of inputting the logistics order information into the logistics cycle model and the logistics cost model to obtain target logistics cycle information and target logistics cost information includes: Determine the shipping address, receiving address, cargo weight, cargo volume, and cargo type based on the logistics order information; Determine the mode of transportation according to the weight of the goods, the volume of the goods and the type of the goods; According to the shipping address, the receiving address and the transportation method, a logistics cycle model is used to predict and obtain target logistics cycle information of each logistics order; The target logistics cost information of each logistics order is obtained by predicting the target logistics cost information of each logistics order based on the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method through the logistics cost model.

3. The method according to claim 2, characterized in that The prediction is performed according to the shipping address, the receiving address and the transportation method through the logistics cycle model to obtain the target logistics cycle information of each logistics order, including: Obtain the order shipment time, and predict the shipment time, unloading completion time, channel warehousing time, channel shipment time, and customer delivery receipt time based on the order shipment time, shipping address, delivery address, and transportation method; Determine the factory delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order based on the order delivery time, the predicted delivery time, the unloading completion time, the channel warehousing time, the channel delivery time and the customer delivery receipt time; The target logistics cycle information of each logistics order is obtained by predicting the delivery cycle, in-transit cycle, short-haul cycle, warehousing cycle and distribution cycle of each logistics order through the logistics cycle model.

4. The method according to claim 3, characterized in that The logistics cycle model is: Among them, T total is the target logistics cycle information predicted by the logistics cycle model, T prod is the factory cycle, T transit is the transit period, T shorthaul is the short-haul cycle, T storage is the storage cycle, T dislivery is the distribution cycle, ω1, ω2, ω3, ω4, ω5 are the weights of the factory cycle, in-transit cycle, short-haul cycle, storage cycle and distribution cycle respectively, γ is the interaction effect between the in-transit cycle and the short-haul cycle, T prod (t-1) is the factory cycle at the previous moment, δ is the hysteresis coefficient, E is the environmental factor, and θ is the adjustment coefficient.

5. The method according to claim 2, characterized in that The target logistics cost information of each logistics order is obtained by predicting the shipping address, the receiving address, the cargo weight, the cargo volume, the cargo type and the transportation method through a logistics cost model, including: Determine the transportation fee, storage fee, packaging fee and insurance fee according to the shipping address, the receiving address, the weight of the goods, the volume of the goods, the type of goods and the mode of transportation; The transportation costs, storage costs, packaging costs and insurance costs are predicted through a logistics cost model to obtain target logistics cost information for each logistics order.

6. The method according to claim 5, characterized in that The logistics cost model is: Among them, C total The target logistics cost information predicted by the logistics cost model, is the transportation cost of the i-th logistics order, is the storage fee of the i-th logistics order, is the packaging cost of the i-th logistics order, is the insurance cost of the i-th logistics order, α0 is the basic logistics cost, α1, α2, α3, α4 are the impact coefficients of transportation cost, warehousing cost, packaging cost and insurance cost respectively, X i is the characteristic vector of the i-th logistics order, β is X i The coefficient vector composed of the coefficients of each feature in , λ1 is the timeliness factor of the i-th logistics order The coefficient of λ2 is the seasonal factor of the i-th logistics order. The coefficient of σ is the customer historical cost of the i-th logistics order θ jk is the coefficient of the feature interaction term, indicating that feature X ij and X ik The interaction between them.

7. The method according to any one of claims 1 to 6, characterized in that The determining of the target delivery path based on the target logistics cycle information and the target logistics cost information includes: Determining the delivery priority of each logistics order based on the target logistics cycle information and the target logistics cost information; Performing route planning according to the delivery priority of each logistics order and the corresponding delivery address to obtain multiple delivery routes; Iteratively optimize each of the distribution paths, with the goal of minimizing the total logistics cost and the total logistics cycle, and select the target distribution path.

8. A logistics control device, characterized in that: The logistics control device comprises: Acquisition module, used to obtain logistics order information; An input module, used to input the logistics order information into a logistics cycle model and a logistics cost model to obtain target logistics cycle information and target logistics cost information; A determination module, configured to determine a target delivery path based on the target logistics cycle information and the target logistics cost information; The distribution module is used to distribute logistics orders based on the target distribution path to achieve the management and control of logistics cycle and logistics cost.

9. A logistics control device, characterized in that: The logistics control device includes: a memory, a processor, and a logistics control program stored in the memory and executable on the processor, wherein the logistics control program is configured to implement the logistics control method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a logistics control program, and when the logistics control program is executed by the processor, the logistics control method according to any one of claims 1 to 7 is implemented.

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