Logistics transportation order combination allocation method
By optimizing logistics transportation order combinations through multi-dimensional classification and heuristic algorithms, the problem of vehicle-cargo mismatch is solved, transportation efficiency and cost-effectiveness are improved, and the system is adapted to complex logistics environments.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- HANSHAN NORMAL UNIV
- Filing Date
- 2024-12-12
- Publication Date
- 2026-05-07
AI Technical Summary
There are problems in the allocation of logistics transportation orders, such as mismatch between vehicles and goods, complex manual scheduling, low transportation efficiency, high costs and unbalanced driver salaries. Existing methods have failed to effectively solve the multi-dimensional matching of vehicle type restrictions and cargo carrying requirements.
A multi-dimensional classification method is adopted, combined with heuristic algorithms and preset allocation rules, taking into account vehicle type restrictions and cargo carrying requirements. Order data is obtained through regular expressions and API interfaces, and greedy algorithms and backtracking optimization methods are used to combine orders and optimize transportation routes and costs.
It has achieved efficient utilization of vehicle resources, reduced transportation costs, improved transportation efficiency, adapted to diversified logistics needs, and reduced empty load rate and transportation time.
Smart Images
Figure CN2024138640_07052026_PF_FP_ABST
Abstract
Description
A method for combining and allocating logistics transportation orders
[0001] This application claims priority to Chinese Patent Application No. 202411540397.3, filed on October 31, 2024, entitled "A Method for Combining and Allocating Logistics Transportation Orders", the entire contents of which are incorporated herein by reference. Technical Field
[0002] This application belongs to the field of logistics and transportation technology, and specifically relates to a method for allocating logistics and transportation order combinations. Background Technology
[0003] In today's globalized economic environment, the logistics industry, as a vital pillar of economic development, is crucial for efficient operation. The rational combination and allocation of logistics transportation orders directly impacts the operating costs, service quality, and market competitiveness of logistics companies.
[0004] Currently, there are numerous problems in the allocation of logistics transportation orders. On the one hand, different vehicle models vary significantly in size, load capacity, and fuel consumption. If order allocation is not considered in light of vehicle type restrictions, it may lead to vehicle overloading, wasted space, or vehicles unsuitable for transporting specific goods. On the other hand, some goods themselves have load-bearing requirements, such as specifying vehicle types or prohibiting stacking. Some logistics transportation companies also face their own pain points. First, their business rules are complex, lacking professional software systems to support dispatching departments, resulting in heavy manual dispatching that often takes a long time. Second, with limited dispatching personnel, it is difficult to optimize the allocation of logistics transportation orders, improve transportation efficiency, and reduce transportation costs. Finally, unreasonable order consolidation in logistics transportation may lead to imbalances in driver compensation and workload, affecting the long-term development of the company.
[0005] To address the aforementioned problems, although numerous logistics order consolidation methods have been proposed, in some cases they either only consider order merging while ignoring vehicle differences, or only dispatch vehicles of different models while ignoring order differences. To overcome these issues, this invention proposes a logistics transportation order combination and allocation method that considers vehicle model restrictions and cargo carrying requirements, specifically addressing the order consolidation problem in the logistics transportation industry. Summary of the Invention
[0006] Based on this, the purpose of this application is to provide a logistics transportation order combination allocation method. By considering vehicle type restrictions and cargo carrying requirements in the logistics transportation order combination allocation, it is possible to make full use of vehicle resources, improve transportation efficiency, and reduce transportation costs, which is of great significance for promoting the sustainable development of the logistics industry.
[0007] To achieve the above objectives, this application provides a method for allocating logistics transportation orders, comprising the following steps:
[0008] Step S1: Obtain the cargo order form, transportation route direction form, and transportation vehicle form;
[0009] Step S2: Based on the cargo order table, obtain the data of delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, and cargo stacking requirements for each order; based on the delivery address of each order and the transportation route direction table, determine the transportation direction to which the delivery address of each order belongs; based on the transportation vehicle table, obtain the data of vehicle type, maximum load capacity, and maximum capacity for each vehicle.
[0010] Step S3: Classify each order according to the shipping direction of the delivery address, vehicle type requirements, cargo carrying method, and cargo stacking requirements to obtain several order combinations;
[0011] Step S4: Using a heuristic algorithm and preset allocation rules, assign all orders in the order combination to the vehicles in the transportation vehicle table to obtain several transportation order combinations;
[0012] Step S5: Merge and optimize the transportation order combinations, and calculate the total transportation mileage and total transportation cost of the optimized transportation order combinations.
[0013] Furthermore, step S2 includes the following steps:
[0014] Step S21: Using regular expressions and keyword matching, extract data such as delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, and cargo stacking requirements for each order from the cargo order table;
[0015] Step S22: Use an external API interface to parse the shipping address data of each order into the corresponding longitude and latitude coordinates;
[0016] Step S23: Compare the longitude and latitude coordinates corresponding to the delivery address of each order with the transportation route direction table to determine the transportation direction to which the delivery address of each order belongs.
[0017] Furthermore, step S23 includes the following steps:
[0018] Step S231: Obtain the longitude and latitude coordinates of the departure point, destination, and reference points along the way for each transportation direction in the transportation route direction table;
[0019] Step S232: Calculate the distance between the delivery address of each order and all reference points or destinations along the shipping routes in the shipping route table. The specific calculation formula is as follows:
[0020] Where R is the Earth's radius, taken as 6371 kilometers, and φ r φ represents the latitude coordinates of reference points or destinations along the route in each transport direction. d The latitude and longitude coordinates of the shipping address for each order, λ r λ represents the longitude coordinates of reference points or destinations along the route in each direction of transport. d The longitude coordinates of the delivery address for each order;
[0021] Step S233: By comparing the calculation results, the shortest intermediate reference point or destination to the delivery address of each order is obtained, and each order is classified into the corresponding transportation direction of the intermediate reference point or destination, thus determining the transportation direction to which the delivery address of each order belongs.
[0022] Furthermore, step S3 includes the following steps:
[0023] Step S31: Order Feature Extraction and Definition: Order features include the shipping direction of the delivery address, vehicle type requirements, cargo loading method, and cargo stacking requirements for each order, respectively labeled as D. i V i W i S i , where i = 1, 2...n, and i represents the number of the i-th order;
[0024] Step S32: Classify each order according to the shipping direction of the delivery address, vehicle type requirements, cargo carrying method, and cargo stacking requirements, and construct a dictionary based on the classification results;
[0025] The dictionary keys are categories including transport direction, vehicle type requirements, cargo loading method, and cargo stacking requirements, tagged as (D i V i W i ,S i The dictionary contains a set of all orders in the corresponding category.
[0026] Furthermore, the heuristic algorithm includes a greedy algorithm and a backtracking optimization method. The specific method of using a heuristic algorithm and a preset allocation rule to allocate all orders in the order combination to the vehicles in the transport vehicle table includes: allocating the orders in each order combination to the vehicles in the transport vehicle table in descending order of the number of cargo carrying units.
[0027] The preset allocation rules include: the total weight of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum load capacity; the total volume of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum capacity; the transportation direction of the orders allocated to each vehicle is consistent; the vehicle type of the orders allocated to each vehicle is consistent; the cargo carrying method of the orders allocated to each vehicle is consistent; the cargo stacking requirements of the orders allocated to each vehicle are consistent; and the number of orders allocated to each vehicle does not exceed a preset value. The volume of the goods in each order can be calculated based on the cargo carrying method and the number of cargo carrying units.
[0028] Furthermore, step S5 includes the following steps:
[0029] Step S51: Merge all transport order combinations that have the same route in the transport direction. If the merged transport order combination meets all the conditions except for the transport direction, the merger is successful.
[0030] Step S52: Sort the transport order combinations in descending order of the remaining load capacity of each vehicle in all transport order combinations, and select the transport order combinations with a remaining load capacity greater than zero as the first set; Sort the transport order combinations in ascending order of the total weight of the goods in all transport order combinations, and select the transport order combinations with a total weight of the goods less than or equal to the maximum remaining load capacity in the first set as the second set.
[0031] The transport order combinations from the first set and the transport order combinations from the second set, including those with vehicle type requirements and those without, are merged. In other words, the orders from the transport order combinations in the second set are attempted to be merged and assigned to the vehicles in the transport order combinations in the first set. If the transport order combinations in the first set meet all the conditions except for the vehicle type requirements after merging, it indicates that the merging is successful.
[0032] Step S53: Based on the distance between the delivery address and the departure point of the transport vehicle for several orders in each transport order combination, adjust the order of several orders in each transport order combination in ascending order;
[0033] Step S54: Calculate the total transportation mileage and total transportation cost of all transportation vehicles based on the merged, optimized, and sorted transportation order combinations, and analyze and optimize based on the calculation results.
[0034] Furthermore, step S5: After merging and optimizing the transportation order combinations and calculating the total transportation mileage and total transportation cost of the optimized transportation order combinations, the logistics transportation order combination allocation method further includes:
[0035] Step S6: Based on the merged and optimized transport order combination, control each transport vehicle to load goods and transport them to the corresponding delivery address in accordance with the cargo carrying method, cargo carrying unit quantity and cargo stacking requirements of its corresponding order.
[0036] According to the specific embodiments provided in this application, the following technical effects are disclosed:
[0037] 1. This application considers a multi-dimensional matching of vehicle type restrictions and cargo carrying requirements: By introducing features such as vehicle type requirements, cargo carrying methods, and stacking capacity into the order, this application enables multi-dimensional classification, allowing each order to be reasonably categorized according to its specific requirements. This multi-dimensional classification method effectively solves the problem of mismatch between different vehicle types and cargo characteristics in logistics transportation, avoiding the waste of transportation capacity and increased costs caused by vehicle-cargo incompatibility.
[0038] 2. Order Grouping Optimization Based on Heuristic Algorithms: This application employs heuristic and backtracking optimization algorithms for order grouping, enabling the finding of near-optimal order combination schemes in a short time. Through rapid calculation and local optimization, it can improve vehicle loading efficiency, minimize empty load rates, and reduce transportation costs. Furthermore, the algorithm design is simple, computationally fast, and suitable for real-time processing of large-scale orders.
[0039] 3. Flexible handling of diverse cargo characteristics and logistics needs: This application introduces preset allocation rules for grouping orders, enabling dynamic adjustment of allocation schemes based on different cargo carrying methods, stacking requirements, etc. This allows the system to flexibly handle different types of cargo, support diverse logistics needs, and enhance the adaptability of allocation schemes. Compared to traditional single-standard allocation methods, this application can handle more complex logistics environments, improving the practicality and scalability of allocation schemes.
[0040] Instruction manual illustrations
[0041] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0042] Figure 1 is a flowchart of this application;
[0043] Figure 2 is a comparison chart of the total mileage calculated using the methods described in this application and existing manual methods for allocating logistics transportation orders within one month. Detailed Implementation
[0044] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0045] The purpose of this application is to provide a method for allocating logistics transportation order combinations.
[0046] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0047] As shown in Figure 1, a logistics transportation order combination allocation method of this application includes the following steps:
[0048] Step S1: Obtain the goods order form, transportation route direction form, and transportation vehicle form.
[0049] Specifically, the cargo order form, transportation route direction form, and transportation vehicle form are all in tabular form.
[0050] The cargo order form records the delivery address, cargo handling method, cargo stacking requirements, vehicle type requirements, and the number of cargo handling units.
[0051] The delivery address is indicated by province and city, such as "Wuhan, Hubei". Cargo carrying methods include long pallets, pallets, square pallets, and cartons. The number of cargo carrying units is related to the carrying method. If long pallets, pallets, or square pallets are used, the number of carrying units is the number of pallets, such as "one pallet" or "two pallets"; if cartons are used, the number of carrying units is the number of cartons, such as "one carton" or "two cartons". Because pallets and cartons are generally customized, the total volume occupied by the cargo can be calculated based on the carrying method and the number of carrying units. Cargo stacking requirements include whether it can be stacked or not. Vehicle type requirements include large trucks, container trucks, flatbed trucks, and restrictions such as "no high-sided or low-bed trailers," "no containers," and "containers are allowed." Some cargo has more lenient vehicle requirements, allowing any vehicle type.
[0052] Specifically, as shown in Table 1, the original goods order form typically summarizes the relevant requirements for goods transportation in the "Operational Requirements" field, including requirements such as the method of carrying goods, stacking requirements, and vehicle type requirements. It may also include some special operational requirements and related notes during transportation, such as delivery deadlines and precautions against water damage. In some embodiments, these special operational requirements can also be used as one of the criteria for order classification and allocation.
[0053] Table 1 Operational Requirements Section of Goods Order Form
[0054] As shown in Table 2, the transportation route direction table is preset based on historical data. It records multiple transportation destinations using provinces, cities, or combinations of provinces and cities, primarily provinces and cities with frequent transportation. Different transportation destinations represent different transportation directions. It also records the departure point, destination, and the longitude and latitude of preset intermediate reference points. Intermediate reference points are generally selected from key locations such as city centers, transportation hubs, and transit hubs along the route. Multiple reference points are recorded whenever possible to minimize the distance between intermediate reference points and the order's delivery address, thereby facilitating transshipment and reducing total transportation mileage and costs. When vehicles have different transportation destinations, the routes they travel on may be the same or have overlapping relationships (e.g., passing through the same toll booths or highway sections). Therefore, orders with different transportation directions but sharing the same transportation routes can be merged later.
[0055] Table 2. Transportation Route Direction Table
[0056] The transport vehicle list records the vehicle type, maximum load capacity, and maximum capacity (i.e., the maximum volume of goods a vehicle can carry) of currently available vehicles. The maximum load capacity and maximum capacity may vary depending on cargo stacking requirements, as the vehicle's load capacity and capacity are reduced when stacking is prohibited. When the currently available vehicles cannot meet the transport needs of an order, new vehicles need to be added based on unassigned orders, and additional vehicles will be dispatched according to the information of these new vehicles.
[0057] Step S2: Based on the cargo order table, obtain the data for each order's delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, and cargo stacking requirements. Based on the delivery address and transportation route direction table for each order, determine the transportation direction to which the delivery address of each order belongs. Based on the transportation vehicle table, obtain the data for each vehicle's vehicle type, maximum load capacity, and maximum capacity.
[0058] Specifically, step S2 includes the following steps:
[0059] Step S21: Using regular expressions and keyword matching, extract data from the goods order table for each order, including delivery address, goods weight, vehicle type requirements, goods carrying method, number of goods carrying units, and goods stacking requirements.
[0060] After obtaining the cargo order table, transportation route direction table, and transportation vehicle table, we can quickly extract key information from the fields recorded in these tables, including the delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, cargo stacking requirements, departure point, destination, and reference points along the route in the transportation route direction table, and vehicle type, maximum load capacity, and maximum capacity of each vehicle in the transportation vehicle table.
[0061] Step S22: Use an external API interface to parse the shipping address data of each order into the corresponding longitude and latitude coordinates.
[0062] Step S23: Compare the longitude and latitude coordinates corresponding to the delivery address of each order with the transportation route direction table to determine the transportation direction to which the delivery address of each order belongs.
[0063] Specifically, step S23 includes the following steps:
[0064] Step S231: Obtain the longitude and latitude coordinates of the departure point, destination, and reference points along the route for each transportation direction in the transportation route direction table.
[0065] Step S232: Calculate the distance between the delivery address of each order and all reference points or destinations along the shipping routes in the shipping route table. The specific calculation formula is as follows:
[0066] Where d is the distance between the delivery address and the reference point or destination along the transportation route in the transportation route direction table, R is the Earth's radius, taken as 6371 kilometers, and φ r φ represents the latitude coordinates of reference points or destinations along the route in each transport direction. d The latitude and longitude coordinates of the shipping address for each order, λ r λ represents the longitude coordinates of reference points or destinations along the route in each direction of transport. d The longitude coordinates of the delivery address for each order.
[0067] Specifically, the above calculation formula assumes that the Earth's surface is a sphere and uses the great circle distance formula to calculate the distance between two points.
[0068] Step S233: By comparing the calculation results, the shortest intermediate reference point or destination to the delivery address of each order is obtained, and each order is classified into the corresponding transportation direction of the intermediate reference point or destination, thus determining the transportation direction to which the delivery address of each order belongs.
[0069] Specifically, the distance between the delivery address of each order and all intermediate reference points or destinations in the shipping route direction table is calculated. After comparing all the calculation results, the nearest intermediate reference point or destination to the delivery address of each order can be found, which can be represented as:
[0070] Here, Υ is a set of preset route tables.
[0071] By using the API interface of an external map platform / software, the delivery address of each order is converted into corresponding longitude and latitude data. Then, based on the longitude and latitude data, it is compared with the longitude and latitude of the departure point, destination, and intermediate reference points in the preset transportation route direction table. If the route direction of the delivery address of each order is closest to a certain intermediate reference point or destination in a certain transportation direction in the transportation route direction table, the order can be classified into that route direction.
[0072] After collecting the above data, by deleting irrelevant fields from the cargo order table and adding fields such as "direction of transport", "latitude and longitude of departure point", "latitude and longitude of destination", and "mileage", a new, concise and clear cargo order table can be created based on the original cargo order table.
[0073] As shown in Table 3, step S3: classify each order according to the transportation direction, vehicle type requirements, cargo carrying method, and cargo stacking requirements of the delivery address of each order to obtain several order combinations.
[0074] Table 3 shows the order combination table obtained after order classification.
[0075] Specifically, step S3 includes the following steps:
[0076] Step S31: Order Feature Extraction and Definition: Order features include the shipping direction of the delivery address, vehicle type requirements, cargo loading method, and cargo stacking requirements for each order, respectively labeled as D. i V i W i S i , where i = 1, 2...n, and i represents the number of the i-th order.
[0077] Step S32: Classify each order according to the shipping direction, vehicle type, cargo carrying method, and cargo stacking requirements of the delivery address, and construct a dictionary based on the classification results.
[0078] The dictionary keys are categories including transport direction, vehicle type requirements, cargo loading method, and cargo stacking requirements, tagged as (D). i Vi W i ,S i The dictionary value is a set of all orders contained in the corresponding category.
[0079] Specifically, in this embodiment, four classification criteria are selected for each order: the direction of transport to the delivery address, vehicle type requirements, cargo carrying method, and cargo stacking requirements. In other embodiments, classification criteria can be added or modified, such as adding delivery deadline requirements. Classifying orders facilitates the subsequent allocation of different orders to transport vehicles. Creating a data structure like a dictionary facilitates rapid processing of the classified data.
[0080] The dictionary formed by classifying all orders, i.e., the grouped dictionary, can be represented as:
[0081] grouped_orders={(D i V i W i ,S i ): Order Collection}
[0082] Here, grouped_orders represents the grouped dictionary.
[0083] Each category may include one or more orders. Specifically, when classifying, a new category is first created based on the first order. If the second order is classified in the same way as the first order, then the second order is assigned to the category of the first order. If they are not the same, a new category is created. This process is repeated for all orders in each category until all orders are classified. This will result in several well-classified order combinations, each of which includes one or more orders.
[0084] In terms of data structures, this means creating a category key Group_Key = D for each order. i V i W i ,S i If the category key already exists in the group dictionary, the order is added to the corresponding group list; if the key does not exist, a new category key is created.
[0085] Since some orders do not have vehicle model requirements, the absence of vehicle model requirements can also be regarded as a classification criterion to group orders with no vehicle model requirements and other identical conditions into one category.
[0086] As shown in Table 4, step S4: Using a heuristic algorithm and preset allocation rules, all orders in all order combinations are allocated to vehicles in the transportation vehicle table to obtain several transportation order combinations.
[0087] Table 4 Transportation Order Combination Table
[0088] Specifically, heuristic algorithms include greedy algorithms and backtracking optimization. A greedy algorithm is a hierarchical processing method that takes the best or optimal (i.e., most advantageous) choice at each step, hoping to lead to a globally optimal result. It is often used to solve optimization problems, especially those that can be decomposed into a series of local choices. For certain types of problems, it can not only find a solution quickly, but often find the optimal solution.
[0089] In this case, the greedy algorithm prioritizes placing orders with larger weight or volume into transport vehicles with sufficient capacity to minimize transportation costs and maximize vehicle utilization. Specifically, in this implementation, assigning orders from all order combinations to vehicles in the transport vehicle table can be considered a Multi-Dimensional Bin Packing Problem (MDBPP), whose goal is to pack a set of orders O = {O1, O2, ..., O...} into vehicles. n} By combining them appropriately, O j For the j-th order, load the most orders into vehicles with limited capacity and load capacity, minimizing the number of vehicles used and the total transportation cost.
[0090] Backtracking optimization is a method for solving problems by trying all possible candidate solutions. It is commonly used to solve combinatorial optimization problems. The core idea is to progressively construct solutions while checking whether candidate solutions satisfy the problem's constraints. If not, backtracking (undoing previous choices) and trying the next candidate solution. Backtracking optimization is advantageous for handling more complex and larger-scale problems and can provide strong support for solving combinatorial optimization problems. In this case, backtracking optimization manifests as assigning an order to a vehicle in the transportation vehicle table and then determining whether the vehicle meets the conditions for transporting the order based on preset allocation rules.
[0091] Specifically, using heuristic algorithms and preset allocation rules, allocating orders from all order combinations to vehicles in the transport vehicle table includes: allocating orders from each order combination to vehicles in the transport vehicle table in descending order of the number of cargo carrying units.
[0092] The preset allocation rules include: the total weight of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum load capacity; the total volume of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum capacity; the transportation direction of the orders allocated to each vehicle is consistent; the vehicle type of the orders allocated to each vehicle is consistent; the cargo carrying method of the orders allocated to each vehicle is consistent; the cargo stacking requirements of the orders allocated to each vehicle are consistent; and the number of orders allocated to each vehicle does not exceed a preset value.
[0093] The preset allocation rules include limiting the number of orders assigned to each vehicle to a preset value (e.g., 3). This is to restrict the number of orders transported by each vehicle, thereby preventing delays due to excessive orders and ensuring the quality of transportation services. The volume of goods in each order can be calculated based on the cargo loading method and the number of cargo loading units. Since pallets and cartons are generally customized and occupy a fixed volume, the total volume occupied by the goods in an order can be calculated by multiplying the volume of the pallet or carton by the number of cargo loading units after knowing the cargo loading method and the number of cargo loading units.
[0094] The specific allocation process is as follows: Assuming the first order is successfully allocated to the first transport vehicle according to the preset allocation rules, a transport vehicle group is created. Simultaneously, the remaining capacity and load capacity of this vehicle are updated, and restrictions are placed on the cargo loading method and stacking requirements within the transport vehicle group. Subsequent orders are also iterated from the first transport vehicle. If the preset allocation rules are also met, the second order is added to the transport vehicle group, and the remaining capacity and load capacity of that vehicle are updated again. This process continues until all orders are allocated. If any transport vehicle's allocated load capacity, capacity, or number of orders has reached its limit, that transport vehicle is removed from the iterated list.
[0095] When all vehicles in the transport vehicle table are allocated or cannot meet the requirements of existing orders, new vehicles are added based on the pending orders, thus creating new transport order combinations. Simultaneously, data for these newly added vehicles is added to the transport vehicle table to facilitate subsequent vehicle dispatching. The vehicle type, load capacity, and capacity of the new vehicles are determined based on template data formed from historical data.
[0096] Step S5: Merge and optimize the transportation order combination, and calculate the total transportation mileage and total transportation cost of the optimized transportation order combination.
[0097] Specifically, step S5 includes the following steps:
[0098] Step S51: Merge all transport order combinations that have the same route in the transport direction. If the merged transport order combination meets the preset allocation rules except for the transport direction, the merger is successful.
[0099] Specifically, having the same route in the direction of transport means that the route taken by the vehicle transport route in one transport order combination is completely identical to the route taken by the vehicle transport route in another transport order combination, or the former completely contains the latter, or the latter completely contains the former.
[0100] Step S52: Sort the transport order combinations in descending order of the remaining load capacity of each vehicle in all transport order combinations, and select the transport order combinations with a remaining load capacity greater than zero as the first set; Sort the transport order combinations in ascending order of the total weight of the goods in all transport order combinations, and select the transport order combinations with a total weight of the goods less than or equal to the maximum remaining load capacity in the first set as the second set.
[0101] The transport order combinations from the first set and the transport order combinations from the second set, including those with vehicle type requirements and those without, are merged. In other words, the orders from the transport order combinations in the second set are attempted to be merged and assigned to the vehicles in the transport order combinations in the first set. If the transport order combinations in the first set meet all the preset assignment rules except for the vehicle type requirement after merging, it indicates that the merging is successful.
[0102] Specifically, this step essentially involves merging transport orders with and without vehicle type requirements. By combining transport orders without vehicle type requirements with transport orders that have vehicle type requirements, the transport orders with vehicle type requirements are then converted into transport orders with vehicle type requirements.
[0103] By sorting and filtering transport order combinations, computational workload can be reduced, facilitating subsequent merging of these combinations. Sorting removes combinations that do not meet certain criteria, such as those with zero remaining load capacity or total cargo weight exceeding the maximum remaining load capacity. This improves merging efficiency and avoids unnecessary mergers. Then, all transport order combinations are iterated through to maximize the utilization of all vehicle capacity and load capacity. Alternatively, transport order combinations can be sorted in descending order of remaining capacity for each vehicle.
[0104] In addition, if the orders in a vehicle of a certain transport order combination are all merged into vehicles of other transport order combinations, then that transport order combination needs to be deleted.
[0105] In other implementations, it is also possible to combine transport orders with and without stacking requirements, for example, placing goods with stacking requirements on one side of the vehicle and goods without stacking requirements on the other side of the vehicle.
[0106] Step S53: Based on the distance between the delivery address and the departure point of the transport vehicle for several orders in each transport order combination, adjust the order of several orders in each transport order combination in ascending order.
[0107] Specifically, by adjusting the transportation order of each order in each transportation order combination, it is easier for transport vehicles to transport the goods according to the adjusted order, thereby saving transportation mileage and transportation costs.
[0108] Step S54: Calculate the total transportation mileage and total transportation cost of all transportation vehicles based on the merged, optimized, and sorted transportation order combinations, and analyze and optimize based on the calculation results.
[0109] Specifically, after merging and optimizing, the transportation route of each transportation order combination is evaluated, and the transportation mileage and total transportation cost of the combination are calculated. The total transportation cost includes toll fees, fuel consumption and other expenses, which can be directly or indirectly related to the transportation mileage. That is, the smaller the transportation mileage, the lower the total transportation cost.
[0110] By calculating the total transport mileage and total transport cost of all vehicles in the optimized transport order combination, and then comparing these data with the total transport mileage and total transport cost obtained using traditional methods for order allocation and combination, we can determine the extent to which the optimized transport order combination can save transport mileage and transport costs. Furthermore, we can further analyze and adjust based on the optimization results to continuously improve the logistics transport order combination.
[0111] In an exemplary embodiment, step S54 specifically involves outputting the sorted transport order combination as the merged and optimized transport order combination.
[0112] Step S6: Based on the merged and optimized transport order combination, control each transport vehicle to load goods and transport them to the corresponding delivery address in accordance with the cargo carrying method, cargo carrying unit quantity and cargo stacking requirements of its corresponding order.
[0113] As shown in Figure 2, the triangle represents the total logistics mileage for each day of the month when orders are allocated using the existing manual order-grouping method, while the dotted line represents the total logistics mileage for each day of the month when orders are allocated using the logistics order combination allocation method of this application. It can be clearly seen that the dotted line is always below the triangle, thus demonstrating that the logistics order combination allocation method of this application can effectively save the total logistics mileage compared to the existing manual order-grouping method, thereby effectively saving logistics costs.
[0114] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.
[0115] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for combining and allocating logistics transportation orders, characterized in that, Includes the following steps: Step S1: Obtain the cargo order form, transportation route direction form, and transportation vehicle form; Step S2: Based on the cargo order table, obtain the data of delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, and cargo stacking requirements for each order; based on the delivery address of each order and the transportation route direction table, determine the transportation direction to which the delivery address of each order belongs; based on the transportation vehicle table, obtain the data of vehicle type, maximum load capacity, and maximum capacity for each vehicle. Step S3: Classify each order according to the shipping direction of the delivery address, vehicle type requirements, cargo carrying method, and cargo stacking requirements to obtain several order combinations; Step S4: Using a heuristic algorithm and preset allocation rules, assign all orders in the order combination to the vehicles in the transportation vehicle table to obtain several transportation order combinations; Step S5: Merge and optimize the transportation order combinations, and calculate the total transportation mileage and total transportation cost of the optimized transportation order combinations.
2. The logistics transportation order combination and allocation method according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Using regular expressions and keyword matching, extract data such as delivery address, cargo weight, vehicle type requirements, cargo carrying method, number of cargo carrying units, and cargo stacking requirements for each order from the cargo order table; Step S22: Use an external API interface to parse the shipping address data of each order into the corresponding longitude and latitude coordinates; Step S23: Compare the longitude and latitude coordinates corresponding to the delivery address of each order with the transportation route direction table to determine the transportation direction to which the delivery address of each order belongs.
3. The logistics transportation order combination and allocation method according to claim 2, characterized in that, Step S23 includes the following steps: Step S231: Obtain the longitude and latitude coordinates of the departure point, destination, and reference points along the way for each transportation direction in the transportation route direction table; Step S232: Calculate the distance between the delivery address of each order and all reference points or destinations along the shipping routes in the shipping route table. The specific calculation formula is as follows: Where R is the Earth's radius, taken as 6371 kilometers, and φ r φ represents the latitude coordinates of reference points or destinations along the route in each transport direction. d The latitude and longitude coordinates of the shipping address for each order, λ r λ represents the longitude coordinates of reference points or destinations along the route in each direction of transport. d The longitude coordinates of the delivery address for each order; Step S233: By comparing the calculation results, the shortest intermediate reference point or destination to the delivery address of each order is obtained, and each order is classified into the transportation direction to which the intermediate reference point or destination belongs, thus determining the transportation direction to which the delivery address of each order belongs.
4. The logistics transportation order combination and allocation method according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Order Feature Extraction and Definition: Order features include the shipping direction of the delivery address, vehicle type requirements, cargo loading method, and cargo stacking requirements for each order, respectively labeled as D. i V i W i S i , where i = 1, 2...n, and i represents the number of the i-th order; Step S32: Classify each order according to the shipping direction of the delivery address, vehicle type requirements, cargo carrying method, and cargo stacking requirements, and construct a dictionary based on the classification results; The dictionary keys are categories including transport direction, vehicle type requirements, cargo loading method, and cargo stacking requirements, tagged as (D i V i W i ,S i The dictionary contains a set of all orders in the corresponding category.
5. A method for combining and allocating logistics transportation orders according to any one of claims 1-4, characterized in that, The heuristic algorithm includes a greedy algorithm and a backtracking optimization method. The specific method of using a heuristic algorithm and a preset allocation rule to allocate orders in all order combinations to vehicles in the transportation vehicle table includes: allocating orders in each order combination to vehicles in the transportation vehicle table in descending order of the number of cargo carrying units. The preset allocation rules include: the total weight of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum load capacity; the total volume of the goods in the orders allocated to each vehicle is less than or equal to the vehicle's maximum capacity; the transportation direction of the orders allocated to each vehicle is consistent; the vehicle type of the orders allocated to each vehicle is consistent; the cargo carrying method of the orders allocated to each vehicle is consistent; the cargo stacking requirements of the orders allocated to each vehicle are consistent; and the number of orders allocated to each vehicle does not exceed a preset value. The volume of the goods in each order can be calculated based on the cargo carrying method and the number of cargo carrying units.
6. The logistics transportation order combination and allocation method according to claim 5, characterized in that, Step S5 includes the following steps: Step S51: Merge all transport order combinations that have the same route in the transport direction. If the merged transport order combination meets the preset allocation rules except for the transport direction, the merger is successful. Step S52: Sort the transport order combinations in descending order of the remaining load capacity of each vehicle in all transport order combinations, and select the transport order combinations with a remaining load capacity greater than zero as the first set; Sort the transport order combinations in ascending order of the total weight of the goods in all transport order combinations, and select the transport order combinations with a total weight of the goods less than or equal to the maximum remaining load capacity in the first set as the second set. The transport order combinations from the first set and the transport order combinations from the second set, including those with vehicle type requirements and those without, are merged. In other words, the orders from the transport order combinations in the second set are attempted to be merged and assigned to the vehicles in the transport order combinations in the first set. If the transport order combinations in the first set meet all the conditions except for the vehicle type requirements after merging, it indicates that the merging is successful. Step S53: Based on the distance between the delivery address and the departure point of the transport vehicle for several orders in each transport order combination, adjust the order of several orders in each transport order combination in ascending order; Step S54: Calculate the total transportation mileage and total transportation cost of all transportation vehicles based on the merged, optimized, and sorted transportation order combinations, and analyze and optimize based on the calculation results.
7. The logistics transportation order combination and allocation method according to claim 1, characterized in that, Step S5: After merging and optimizing the transportation order combinations and calculating the total transportation mileage and total transportation cost of the optimized transportation order combinations, the logistics transportation order combination allocation method further includes: Step S6: Based on the merged and optimized transport order combination, control each transport vehicle to load goods and transport them to the corresponding delivery address in accordance with the cargo carrying method, cargo carrying unit quantity and cargo stacking requirements of its corresponding order.