A method for cargo storage location allocation and inbound route planning

Abstract

This invention discloses a method for cargo storage location allocation and inbound route planning, belonging to the fields of logistics management and warehousing. The method includes: acquiring cargo data and candidate storage locations; calculating cargo priorities; generating an initial solution based on priorities; constructing a function to measure the matching degree between cargo and storage locations; constructing a function to evaluate storage location allocation schemes; using a simulated annealing algorithm to obtain multiple sets of storage location allocation schemes; planning inbound routes for each allocation result and calculating the total inbound distance; and selecting the allocation result with the shortest total path as the final result. This method takes into account both storage location allocation and inbound route planning, solving the problems of unreasonable storage location allocation and irregular cargo storage, reducing the walking distance for inbound operations, and improving the utilization rate of warehouse space.

Description

Technical Field

[0001] This invention discloses a method for allocating cargo storage locations and planning inbound routes, belonging to the field of logistics management and warehousing. Background Technology

[0002] With the rapid development of the logistics sector, enterprises are placing higher demands on the efficiency of warehousing operations. Inbound storage is a crucial part of warehousing operations. Traditional warehousing management often relies on the experience of operators to allocate storage locations. Manual management requires high levels of skill and experience from operators, and manual allocation of storage locations is prone to duplicate allocations, incorrect allocations, and low efficiency, significantly impacting warehousing management efficiency and increasing labor costs.

[0003] Many logistics companies have begun to pay attention to issues in warehouse management, and have explored and researched warehouse location allocation and determining inbound routes, proposing some solutions. The inbound process consists of a series of small operations, but existing systems and methods often only consider warehouse location allocation or only determine the inbound order, without considering both in combination.

[0004] A search revealed a Chinese patent, "A Storage Location Allocation Method, System, and Medium Based on an Improved Fruit Fly Optimization Algorithm" (Application Publication Date: January 9, 2024; Application No.: CN202210695961.3). The method includes: acquiring basic information about target goods; determining the goods to be stored within a target period and the remaining storage space on the stacker crane within the target goods; determining the optimal placement position of the goods to be stored within the target period based on the goods to be stored, the remaining space, and the improved fruit fly optimization algorithm, thus completing the stacker crane storage location allocation for the goods to be stored. This patent achieves storage location allocation but does not determine the storage path for the goods.

[0005] A search revealed a Chinese patent, "A Method and System for Warehouse Goods Inbound Management" (Application Publication Date: May 23, 2023; Application No.: CN202310433608.2). This method includes: collecting RFID electronic tags from goods to be inbound and generating weights for the goods; dividing the warehouse shelves into areas to obtain several storage locations; determining the storage location corresponding to the goods to be inbound; determining the transport dimensions of the goods to be inbound; and determining the appropriate storage shelf from among the several storage locations to complete the goods inbound process. This warehouse goods inbound management method constructs an inbound allocation model, using the maximum accommodating size of goods at each grid node and the transport dimensions of the goods to be inbound as inputs to the model, thereby enabling the selection of the shelf with the shortest transport distance during the goods inbound process. While this patent achieves storage location allocation and considers the transport distance during the inbound process, it does not plan the goods inbound route.

[0006] The allocation of warehouse locations often involves how to rationally plan the order and route of goods entering the warehouse in order to improve operational efficiency and reduce handling distances and time costs. Therefore, an effective method for allocating warehouse locations and planning inbound routes is of great significance for improving warehousing efficiency. Summary of the Invention

[0007] To address the problems of existing cargo allocation methods being overly reliant on manual labor, having unreasonable warehouse location allocation, and exhibiting no fixed storage patterns, this invention provides a method that balances warehouse location allocation with the shortest inbound route. This ensures that when planning inbound routes for multiple goods, the transportation distance within the warehouse can be minimized, while also considering route planning schemes for cross-warehouse areas.

[0008] To solve the above problems, the present invention adopts the following technical solution.

[0009] A method for allocating warehouse locations and planning inbound routes, the method comprising:

[0010] 1. Obtain cargo data and alternative storage locations, calculate the priority for each cargo, and generate an initial allocation result based on the cargo priority;

[0011] 2. Construct a function E(X) to measure the degree of matching between goods and allocated storage locations;

[0012] 3. Construct the function cost(X) to evaluate the storage location allocation scheme;

[0013] IV. Set different initial parameters T, use simulated annealing algorithm to optimize the initial solution, and obtain multiple sets of storage location allocation results;

[0014] 5. Plan the shortest inbound path for each storage location allocation scheme and calculate the path length;

[0015] 6. Select the storage location allocation scheme with the shortest total path and determine the final result.

[0016] Furthermore, in step S1, for each item, its priority is calculated based on its attributes, and an initial solution is generated based on the item priority, specifically including:

[0017] S11. Calculate the priority of goods based on their attributes:

[0018] Cargo priority is determined by estimated storage time (t), customer importance (s), cargo value (v), and cargo weight (m). The priority p of the i-th cargo... i The calculation formula is:

[0019] p i =α*(1-t)+β*s+γ*v+δ*(1-m);

[0020] Among them, α, β, γ, and δ are weights;

[0021] S12. Starting with the highest priority goods, select the candidate storage location closest to the starting point. The allocation process continues until all goods are allocated. This allocation result is the initial solution.

[0022] Furthermore, in step S2, a constructor E(X) is constructed to measure the degree of matching between goods and storage locations. The specific calculation method is as follows:

[0023] The matching degree between goods and storage locations, E(X), is measured from aspects such as size matching degree (similarity1(X)), priority and distance between entry and exit points (similarity2(X)), where X is a solution for a set of storage location allocations;

[0024] The formula for similarity1(X) is:

[0025]

[0026] Where V i V j These represent the cargo volume and the storage space volume, respectively, max(L) i ), max(W i ), max(H i ) represents the maximum length, width, and height of the cargo, L j W j H j x represents the length, width, and height of the storage location; ij This indicates whether goods i are placed in storage location j, with a value of 1 or 0; the quantity of goods is N, and the number of alternative storage locations is M.

[0027] The formula for similarity2(X) is:

[0028]

[0029] Where p i For the priority of goods i, p max distancew represents the highest priority among the goods awaiting warehousing. j distanceo j Distancew represents the distance from storage location j to the inbound point and the outbound point, respectively. max This represents the distance from the storage location furthest from the storage point among all candidate storage locations. max This represents the distance from the outbound point to the storage location, x, among all the alternative storage locations. ij This indicates whether item i is placed in storage location j, and its value is 1 or 0.

[0030] The formula for calculating E(X) is as follows:

[0031]

[0032] Where a and b are weights.

[0033] Furthermore, in step S3, a function cost(X) is constructed to evaluate the storage location allocation scheme, specifically including:

[0034] The constructor cost(X) is used to evaluate the storage location allocation scheme. The smaller the cost(X) value, the better the allocation scheme. The factors considered when evaluating the allocation scheme include: storage location area utilization rate (S(X)), storage cost (C(X)), and the suitability between goods and storage location (E(X)).

[0035] The formula for S(X) is:

[0036]

[0037] S i Let S be the area occupied by cargo i. j The area of ​​the storage location is max(W). i ), max(L i ) represents the maximum length and width of the goods, L j W j These are the length and width of storage location j, respectively;

[0038] The formula for C(X) is:

[0039]

[0040] c j t represents the storage cost of location j. i t represents the expected storage time of goods i. max c represents the maximum expected storage time for all goods awaiting warehousing. max This represents the maximum storage cost among all available storage locations.

[0041] The final formula for cost(X) is:

[0042]

[0043] w1, w2, and w3 are weights.

[0044] Furthermore, in step S4, an improved simulated annealing algorithm is used to obtain multiple storage location allocation schemes, specifically including:

[0045] S41. Set the initial parameter T and begin the iteration process;

[0046] S42. Randomly select two goods and exchange their storage location allocation results to obtain a new allocation scheme X. new Calculate cost(X) new And determine whether to accept the new solution X according to the Metropolis criterion. new ;

[0047] S43. Adjust the value of parameter T according to the adjustment coefficient α, where α = e -0.01*k , where k is the k-th iteration;

[0048] S44, Repeat S42 and S43, when T new With T old When the difference is less than the set threshold, the iteration stops and a set of solutions for the allocation of storage locations is obtained;

[0049] S45. Randomly select N different initial parameters within the interval [k*T, r*T], where k and r are constants, and repeat the above steps to obtain N solutions for the allocation of storage locations.

[0050] Furthermore, in step S5, the total path for each solution group is calculated and the final allocation scheme is determined, specifically including:

[0051] S51. Sort all reservoir areas in ascending order according to their distance from the starting point, obtaining a sequence of reservoir areas from nearest to farthest, S1...S... k ;

[0052] S52. Given K storage areas, N allocation results, and N goods, for a certain storage area allocation result X... i , will X i All storage locations are classified according to their respective storage areas, resulting in storage areas S1...S1. N The list of storage locations in List1...List N ;

[0053] S53, in the warehouse location list i In the middle, construct a graph representation of List. i The relationship between all storage locations is shown in the diagram. Each node in the diagram represents a storage location, and the path length is the distance between storage locations.

[0054] S54. Use Dijkstra's algorithm to plan the path and calculate the reservoir area S. j The required routeLength j Determined in reservoir area S j The starting point location begin and the endpoint location end ;

[0055] S55. Repeat steps S53 to S54 in other storage areas to obtain the shortest path to travel in other storage areas.

[0056] S56, Calculate X i The path length of the allocation scheme is lengthTotal. i The specific calculation formula is as follows:

[0057]

[0058] Where routeLength j For the S reservoir area j The required walking distance is distance(j,j+1) for the reservoir area S. j With S j+1 The distance between them, otherLength j For location begin Distance to the entry point plus location end Distance to the outbound point;

[0059] S57, Select LengthTotal i The smallest group is the final allocation result.

[0060] Furthermore, based on the final warehouse location allocation results, inbound route planning is performed, specifically as follows:

[0061] Regarding the final storage location allocation result X end First, starting from the initial entry point, proceed to the first storage area S1. Following the planned route, the goods are stored in storage area S1. Once all goods in storage area S1 are stored, the same process is repeated in other storage areas. When S... N Once the warehousing operation in the warehouse area is completed, the warehousing process ends.

[0062] Beneficial effects

[0063] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0064] This invention discloses a method for goods storage location allocation and inbound route planning. It collects data on goods awaiting inbound storage from the field, uses a simulated annealing algorithm to generate multiple storage location allocation schemes, and selects the scheme with the shortest total inbound route as the final storage location allocation result. By comprehensively considering both storage location allocation and the shortest inbound route, the final inbound order is determined. This method helps enterprises reduce their reliance on manual experience in inbound operations, reducing personnel and time costs, solving problems such as unreasonable storage location allocation and irregular goods storage, improving operational efficiency, and promoting the long-term development of enterprises. Attached image description:

[0065] Figure 1 This is a flowchart of the storage location allocation method and inbound path planning described in this embodiment;

[0066] Figure 2 A flowchart for generating multiple sets of storage location allocation results in step S4;

[0067] Figure 3 A flowchart for planning the inbound path in step S5. Detailed Implementation

[0068] The present invention will now be further described with reference to specific embodiments and accompanying drawings.

[0069] A method for goods storage location allocation and inbound route planning is presented. This method collects data on goods to be stored and uses a simulated annealing algorithm to obtain multiple storage location allocation schemes. The scheme with the shortest total inbound route is selected as the final result. The specific process and effects are described in detail below.

[0070] like Figures 1 to 3 As shown, the method mainly includes the following steps:

[0071] 1. Obtain cargo data and alternative storage locations, calculate the priority for each cargo, and generate an initial allocation result based on the cargo priority;

[0072] S11. Calculate the priority of goods based on their attributes:

[0073] Goods priority is determined by estimated storage time (t), customer importance (s), goods value (v), and goods weight (m). Goods priority is negatively correlated with estimated storage time and goods weight, and positively correlated with customer importance and goods value. All attributes used in the calculation have been normalized. The priority p of the i-th goods... i The calculation formula is:

[0074] p i =α*(1-t)+γ*s+γ*v+δ*(1-m)

[0075] Among them, α, β, γ, and δ are weights.

[0076] S12. Starting with the highest priority goods, select the nearest alternative storage location to the starting point. Here, alternative storage locations refer to available storage locations that meet the goods placement conditions, not all available storage locations. The allocation process continues until all goods have been allocated, and this allocation result is the initial solution.

[0077] 2. Construct a function E(X) to measure the degree of matching between goods and assigned storage locations;

[0078] The matching degree between goods and storage locations, E(X), is measured from aspects such as size matching degree (similarity1(X)), priority and distance between entry and exit points (similarity2(X)), where X is a solution for a set of storage location allocations, and the larger E(X) is, the better the matching degree.

[0079] The formula for similarity1(X) is:

[0080]

[0081] Where V i V j These represent the cargo volume and the storage space capacity, respectively. max(L) i ), max(W i ), max(H i ) represents the maximum length, width, and height of the goods. L j W j H j This represents the length, width, and height of the storage location. ij This indicates whether item i is placed in storage location j, with a value of 1 or 0. The quantity of items is N, and the number of alternative storage locations is M.

[0082] The formula for similarity2(X) is:

[0083]

[0084] Where p i For the priority of goods i, p max distancew represents the highest priority among the goods awaiting warehousing. j distanceo j Distancew represents the distance from storage location j to the inbound point and the outbound point, respectively. max This represents the distance from the storage location furthest from the storage point among all candidate storage locations. max This represents the distance from the outbound point to the storage location, x, among all the alternative storage locations. ij This indicates whether item i is placed in storage location j, and its value is 1 or 0.

[0085] The formula for calculating E(X) is as follows:

[0086]

[0087] Where a and b are weights.

[0088] For example, if N=10 and M=50, the 50 candidate storage locations are distributed across 5 storage areas (numbered A, B, C, D, and E). The entry and exit points are located at storage location 1-1 and storage location 1-10, respectively. The costs of the 5 storage areas are 10, 20, 40, 10, and 1, respectively. The entry point for all storage areas is 1-1, and the exit point is 1-10.

[0089] The generated initial storage location allocation solution is known.

[0090] X0=[A1-1, A4-5, B1-10, B5-3, C3-3, C6-2, D7-3, D10-4, E8-3, E4-6]

[0091] The priorities are [0.85, 0.8, 0.75, 0.7, 0.5, 0.3, 0.3, 0.15, 0.13, 0.1]

[0092] The storage times are [5, 7, 8, 9, 10, 11, 16, 17, 19, 20] in sequence.

[0093] All storage locations have dimensions of 2*2*1. The maximum dimensions of the goods are 2, 2, and 1. The goods are irregularly shaped, occupying an area of ​​3 and having a volume of 3.

[0094] In this example, with a set to 0.4 and b set to 0.6, the calculated value of E(X) is approximately 0.718.

[0095] 3. Construct the function cost(X) to evaluate the storage location allocation scheme;

[0096] The constructor `cost(X)` is used to evaluate the current storage location allocation plan. The smaller the value of `cost(X)`, the better the allocation plan. Factors considered when evaluating the allocation plan include: storage location area utilization rate (S(X)), storage cost (C(X)), and the fit between goods and storage locations (E(X)).

[0097] The formula for S(X) is:

[0098]

[0099] S i Let S be the area occupied by cargo i. j Let W be the area of ​​storage location j, max(W i ), max(L i ) represents the maximum length and width of the goods, L j W j These represent the length and width of storage location j, respectively.

[0100] The formula for C(X) is:

[0101]

[0102] c j t represents the storage cost of location j. i t represents the expected storage time of goods i. max c represents the maximum expected storage time for all goods awaiting warehousing. max This represents the maximum storage cost among all available storage locations.

[0103] The final formula for cost(X) is:

[0104]

[0105] w1, w2, and w3 are weights.

[0106] In this example, w1, w2, and w3 are set to 0.3, 0.3, and 0.4 respectively, and the calculated cost(X0) value is approximately 0.35.

[0107] IV. By setting different initial parameters T, the initial solution is optimized using the improved simulated annealing cycle algorithm to obtain multiple sets of storage location allocation results.

[0108] S41. Set the initial parameter T and begin the iteration process;

[0109] S42. Randomly select two goods and exchange their storage location allocation results to obtain a new allocation scheme X. new Calculate cost(X) new And determine whether to accept the new solution X according to the Metropolis criterion. new ;

[0110] S43. Adjust the value of parameter T according to the adjustment coefficient α, where α = e -0.01*k , where k is the k-th iteration;

[0111] S44, Repeat S42 and S43, when T new With T old When the difference is less than the set threshold, the iteration stops and a set of solutions for the allocation of storage locations is obtained;

[0112] S45. Randomly select N different initial parameters within the interval [k*T, r*T], where k and r are constants, and repeat the above steps to obtain N solutions for the allocation of storage locations.

[0113] 5. Plan the shortest inbound path for each storage location allocation scheme and calculate the path length;

[0114] S51. Sort all reservoir areas in ascending order according to their distance from the starting point, obtaining a sequence of reservoir areas from nearest to farthest, S1...S... k .

[0115] S52. Given K storage areas, N allocation results, and N goods, for a certain storage area allocation result X... i , will X i All storage locations are classified according to their respective storage areas, resulting in storage areas S1...S1. N The list of storage locations in List1...List N ;

[0116] S53, in the warehouse location list i In the middle, construct a graph representation of List. i The relationship between all storage locations is shown in the diagram. Each node in the diagram represents a storage location, and the path length is the distance between storage locations.

[0117] S54. Use Dijkstra's algorithm to plan the path and calculate the reservoir area S. j The required routeLength j Determined in reservoir area S j The starting point location begin and the endpoint location end ;

[0118] S55. Repeat steps S53 to S54 in other storage areas to obtain the shortest path to travel in other storage areas.

[0119] S56, Calculate X i The path length of the allocation scheme is lengthTotal. i The specific calculation formula is as follows:

[0120]

[0121] Where routeLength j For the S reservoir area j The required walking distance is distance(j,j+1) for the reservoir area S. j With S j+1 The distance between them, otherLength j For location begin Distance to the entry point plus location end Distance to the outbound point;

[0122] S57, Select LengthTotal i The smallest group is the final allocation result.

[0123] For example, the storage location allocation result is X1 = [A1-1, A5-1, A5-5, A8-5, B3-3, B6-3, B9-3, E1-6, E8-3, E8-6], the distance between storage areas A and B is 10, and the distance between storage areas B and E is 20.

[0124] For example, in reservoir A, the distance between edges (A1-1, A5-1) is 4, (A5-1, A5-5) is 4, and (A5-5, A8-5) is 3; in reservoir B, the distance between edges (B3-3, B6-3) is 3, and (B6-3, B9-3) is 3; and in reservoir E, the distance between edges (E1-6, E8-3) is 3, and (E8-3, E8-6) is 3.

[0125] routeLength A routeLength B routeLength E The values ​​are 11, 6, and 6 respectively, and otherLength A otherLength B otherLength E The values ​​are 4.47, 5.06, and 10.39 respectively, and the final lengthTotal is... i The value is 72.92.

[0126] VI. Select the storage location allocation scheme with the shortest total path and determine the final result;

[0127] For example, another set of storage location allocation results X2 = [A1-1, A1-10, B2-1, B2-10, C3-1, C3-10, D4-1, D4-10, E8-1, E8-10]. The distance between storage areas A and B is 10, the distance between storage areas B and C is 10, the distance between storage areas C and D is 5, and the distance between storage areas D and E is 20. The entry point for all storage areas is 1-1, and the exit point is 1-10.

[0128] Based on the previous step, the routeLength can be calculated. A routeLength B routeLength C routeLength D routeLength E The values ​​for all are 9, otherLength A otherLength B otherLength C otherLength D otherLengthE The values ​​are 0, 2, 4, 6, and 10 respectively, and the final lengthTotal is... i The value is 112.

[0129] Compared to the allocation result X1 mentioned in the previous step, the path of the allocation result X2 appearing in this step is longer than that of the allocation result mentioned in the previous step. Therefore, the final allocation result is X1 = [A1-1, A5-1, A5-5, A8-5, B3-3, B6-3, B9-3, E1-6, E8-3, E8-6] mentioned in the previous step.

[0130] For the final storage location allocation result X1, firstly, from the starting point of the inbound process to the first storage area S1, the inbound operation is carried out in storage area S1 according to the planned path. After all the goods in storage area S1 are inbound, the operation in other storage areas is carried out in the same way. N Once the warehousing operation in the warehouse area is completed, the warehousing process ends.

Claims

1. A method for allocating warehouse locations and planning inbound routes, characterized in that, include: S1. Obtain cargo data and alternative storage locations, calculate cargo priority, and generate an initial solution based on priority; S2. Construct a function E(X) to measure the degree of matching between goods and storage locations. The specific calculation method is as follows: The degree of matching between goods and storage locations E(X) is determined by the size matching degree. Priority and distance matching between inbound and outbound points The measure is given by X, which is a solution for a set of storage location allocations. The formula is: ; Where V i V j These are the cargo volume and the storage space volume, respectively. , , L represents the maximum length, width, and height of the cargo. j W j H j x represents the length, width, and height of the storage location; ij This indicates whether goods i are placed in storage location j, with a value of 1 or 0; the quantity of goods is N, and the number of alternative storage locations is M. The formula is: ; Where p i For the priority of goods i, p max distancew represents the highest priority among the goods awaiting warehousing. j distanceo j Distancew represents the distance from storage location j to the inbound point and the outbound point, respectively. max This represents the distance from the storage location furthest from the storage point among all candidate storage locations. max This represents the distance from the outbound point to the storage location, x, among all the alternative storage locations. ij This indicates whether item i is placed in storage location j, and its value is 1 or 0. The calculation formula is as follows: Where a and b are weights; S3. Construct the function cost(X) to evaluate the storage location allocation plan. Specifically, the factors considered when evaluating the allocation plan include: storage location area utilization rate S(X), storage cost C(X), and the matching degree between goods and storage locations E(X); the formula for S(X) is: ; S i Let S be the area occupied by cargo i. j The area of ​​the storage location. , L represents the maximum length and width of the cargo. j W j Let x be the length and width of storage location j, respectively; the formula for C(X) is: ; c j t represents the storage cost of location j. i t represents the expected storage time of goods i. max c represents the maximum expected storage time for all goods awaiting warehousing. max The maximum storage cost among all candidate storage locations; cost(X), the formula is: ; Where w1, w2, and w3 are weights; S4. Set different initial parameters T and use the improved simulated annealing algorithm to obtain multiple sets of storage location allocation results; S5. For each group of goods allocation results, plan the inbound route and calculate the route length, and select the group with the shortest total route as the final allocation result.

2. The method for allocating warehouse locations and planning inbound routes according to claim 1, characterized in that, In step S1, for each item, its priority is calculated based on its attributes, and an initial solution is generated based on the item priority. This specifically includes: S11. Calculate the priority of goods based on their attributes: Cargo priority is determined by estimated storage time (t), customer importance (s), cargo value (v), and cargo weight (m). The priority p of the i-th cargo... i The calculation formula is: ； Among them, α, β, γ, and δ are weights; S12. Starting with the highest priority goods, select the candidate storage location closest to the starting point. The allocation process continues until all goods are allocated. This allocation result is the initial solution.

3. The method for allocating warehouse locations and planning inbound routes according to claim 1, characterized in that, In step S4, an improved simulated annealing algorithm is used to obtain multiple storage location allocation schemes, specifically including: S41. Set the initial parameter T and begin the iteration process; S42. Randomly select two goods and exchange their storage location allocation results to obtain a new allocation scheme X. new Calculate cost(X) new And determine whether to accept the new solution X according to the Metropolis criterion. new ; S43. Adjust the value of parameter T according to the adjustment coefficient α, where , where k is the k-th iteration; S44, Repeat S42 and S43, when T new With T old When the difference is less than the set threshold, the iteration stops and a set of solutions for the allocation of storage locations is obtained; S45. Randomly select N different initial parameters within the interval [k*T, r*T], where k and r are constants, and repeat the above steps to obtain N solutions for the allocation of storage locations.

4. The method for allocating warehouse locations and planning inbound routes according to claim 1, characterized in that, In step S5, the total path for each solution group is calculated and the final allocation scheme is determined, specifically including: S51. Sort all reservoir areas in ascending order according to their distance from the starting point, obtaining a sequence of reservoir areas from nearest to farthest, S1...S... k ; S52. Given K storage areas, N allocation results, and N goods, for a certain storage area allocation result X... i , will X i All storage locations are classified according to their respective storage areas, resulting in storage area S. 1…… S N List of storage locations 1…… List N ; S53, in the warehouse location list i In the middle, construct a graph representation of List. i The relationship between all storage locations is shown in the diagram. Each node in the diagram represents a storage location, and the path length is the distance between storage locations. S54. Use Dijkstra's algorithm to plan the path and calculate the reservoir area S. j The required routeLength j Determined in reservoir area S j The starting point location begin and the endpoint location end ; S55. Repeat steps S53 to S54 in other storage areas to obtain the shortest path to travel in other storage areas. S56, Calculate X i The path length of the allocation scheme is lengthTotal. i， The specific calculation formula is as follows: ； Where routeLength j For the S reservoir area j The required walking distance is distance(j,j+1) for the reservoir area S. j With S j+1 The distance between them, otherLength j For location begin Distance to the entry point plus location end Distance to the outbound point; S57, Select LengthTotal i The smallest group is the final allocation result.

5. The method for cargo storage location allocation and inbound route planning according to claim 4, characterized in that, Based on the final warehouse location allocation results, the inbound route is planned in the following way: Regarding the final storage location allocation result X end First, starting from the initial entry point, proceed to the first storage area S1. Following the planned route, the goods are stored in storage area S1. Once all goods in storage area S1 are stored, the same process is repeated in other storage areas. When S... N Once the warehousing operation in the warehouse area is completed, the warehousing process ends.

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