Urban shared bicycle putting method with optimal global benefit

Abstract

The invention discloses an urban shared bicycle putting method with optimal global benefit, belongs to the technical field of shared bicycle dispatching, and is used for solving the problems of high total consumption and low resource utilization rate caused by lack of overall allocation of multiple shared bicycle companies in a city. The method comprises the following three steps. The method comprises the following steps: 1, collecting cost data of a shared bicycle company for putting a shared bicycle to a demand place; 2, establishing a putting model for overall planning of global benefits; and step 3, constructing a putting strategy based on a putting model for overall planning of global benefits. According to the method, unified allocation among a plurality of shared bicycle companies in a city can be planned as a whole, so that the total consumption and the resource use efficiency are more optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of scheduling shared bicycles, and in particular to a method for deploying shared bicycles in a city with optimal global benefits. Background Art

[0002] The importance of shared bicycles in urban transportation is becoming increasingly prominent: alleviating traffic congestion, promoting environmental protection and sustainable development, facilitating travel, reducing travel costs, promoting health, and enhancing the city's image.

[0003] In the existing shared bicycle dispatching technology, the focus is often on the deployment of a single shared bicycle company. For example, in the invention patent with publication number CN118246688A, shared bicycle feature analysis and demand point identification are realized by extracting POI data to solve the problem of matching shared bicycle deployment with demand. The invention patent with publication number CN117217441A flexibly adjusts the deployment of shared bicycles according to different reliability requirements in advance, effectively avoiding waste of resources.

[0004] However, the current related technologies are only for a single shared bicycle company, and cannot be applied to the coordinated deployment of multiple shared bicycle companies in a city. In practice, there may be a lack of unified management among multiple shared bicycle companies in a city, resulting in excessive deployment at some distribution points and insufficient deployment at other distribution points, resulting in a large total cost, wasting social wealth, reducing economic benefits, inefficient use of resources, inconvenience for citizens to travel, and increased urban traffic pressure. Summary of the invention

[0005] The purpose of the present invention is to provide a method for deploying shared bicycles in cities with the best global benefits, so as to solve the problems raised in the above background technology. To achieve the above purpose, the present invention provides a method for deploying shared bicycles in cities with the best global benefits, comprising the following steps:

[0006] Step 1: Collect the cost data of the shared bicycle company deploying a shared bicycle to the demand area; Step 2: Establish a deployment model that coordinates the overall benefits; Step 3: Construct a deployment strategy based on the deployment model that coordinates the overall benefits.

[0007] In the implementation method, the second step of establishing a delivery model for overall benefits is:

[0008]

[0009]

[0010] Among them, p ij is the cost of a shared bicycle company Ci (i = 1, 2, ..., m) to deploy a shared bicycle to the demand location Dj (j = 1, 2, ..., n), x ijis the number of shared bicycles that company Ci plans to deploy to demand location Dj, c i is the number of shared bicycles owned by the shared bicycle company Ci (i=1,2,…,m), d j is the demand for shared bicycles at demand location Dj (j=1,2,…,n)(d j It can be obtained from the prior art, for example, invention patents with publication numbers CN112330205A and CN115936240A provide two different methods).

[0011] Step 3: Based on the delivery model that takes into account the overall benefits, the methods for constructing delivery strategies include:

[0012] 1) Model matrixing: Write the overall benefit delivery model established in step 2 into a matrix form:

[0013] min px

[0014]

[0015] in,

[0016] p=(p 11 ,p 12 ,…,p 1n ,p 21 ,p 22 ,…,p 2n ,…,p m1 ,p m2 ,…,p mn ), x=(x 11 ,x 12 ,…,x 1n ,x 21 ,x 22 ,…,x 2n ,…,x m1 ,x m2 ,…,x mn ) T , E is an n-dimensional row vector whose components are all 1, I is an n-order identity matrix, b=(c 1 ,c 2 ,…,c m ,d 1 ,d 2 ,…,d n ) T , T Represents the transpose of a vector.

[0017] 2) Balance matrix reversibility reorganization: Write the balance matrix A in the form of columns A = (q 1 ,q 2 ,…,q mn) and reorganize into A = (BN) by column transposition so that B is a reversible matrix, and the set of column numbers of N in matrix A is denoted as R; p and x are both reorganized into p = (p B ,p N ) and x=(x B ,x N ).

[0018] 3) Construct the discriminator Δ: Calculate p for each element j in the set R described in 2). B B -1 q j -p j , among these calculated values, let the value p corresponding to the kth element B B -1 q k -p k Maximum, let the discriminator Δ=p B B -1 q k -p k , if Δ≤0, then the best delivery strategy is x=(x B ,x N ), where x B =B -1 b,x N =0, step three ends; otherwise, go to the next step.

[0019] 4) Update the discriminator: for k mentioned in 3), record x' B =B -1 q k x k , remember x B (i) and x' B (i) are x B and x' B The ith element of , calculate x for all i B (i) / x' B (i) Among these calculated values, let the rth value x B (r) / x' B (r) is the largest, then find x B The rth component in, for example, x h ; Then change column q in B k Replace q h , get the updated B, go to 3).

[0020] Beneficial Effects

[0021] The shared bicycle deployment method provided by the present invention coordinates the unified deployment among multiple shared bicycle companies in the city, minimizes the total cost, reduces the waste of social wealth, and increases economic benefits; maximizes the efficiency of resource utilization and facilitates citizens' travel; and alleviates the urban traffic pressure as much as possible, which is conducive to smooth urban traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flow chart of a method for deploying urban shared bicycles with optimal global benefits provided by the present invention;

[0023] Figure 2 A flow chart of the method for constructing a delivery strategy provided by the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the implementation of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] Assume that there are m shared bicycle companies C1, C2, ..., Cm in a city, and the number of shared bicycles owned by each company is c 1 ,c 2 ,…,c m There are n shared bicycle demand areas D1, D2, ..., Dn, and the demand for shared bicycles in each demand area is d 1 ,d 2 ,…,d n , (d 1 ,d 2 ,…,d n It can be obtained from the prior art, for example, invention patents with publication numbers CN112330205A and CN115936240A provide two different methods).

[0026] like Figure 1 As shown, the implementation of the present invention includes three steps.

[0027] Step 1: First, collect the cost p of the shared bicycle company Ci (i = 1, 2, ..., m) to deploy a shared bicycle to the demand location Dj (j = 1, 2, ..., n) ij .

[0028] Step 2: Let x ij is the number of shared bicycles that company Ci plans to put in demand location Dj, using the data p collected in step 1 ij , establish the following delivery model to coordinate overall benefits:

[0029]

[0030]

[0031] Step 3: Based on the overall benefit delivery model established in step 2, build a delivery strategy according to the following steps S1-S4 (such as Figure 2 shown).

[0032] S1: Model matrix. Introduce the following notation:

[0033] p=(p 11 ,p 12 ,…,p 1n ,p 21 ,p 22 ,…,p 2n ,…,p m1 ,p m2 ,…,p mn ), x=(x 11 ,x 12 ,…,x 1n ,x 21 ,x 22 ,…,x 2n ,…,x m1 ,x m2 ,…,x mn ) T , E is an n-dimensional row vector whose components are all 1, I is an n-order identity matrix, b=(c 1 ,c 2 ,…,c m ,d 1 ,d 2 ,…,d n ) T , T Represents the transpose of a vector.

[0034] The overall benefit allocation model established in step 2 can be expressed in the following matrix form:

[0035] min px

[0036]

[0037] S2: Reconstruct the balance matrix A in a reversible way: The first step is to write the balance matrix A in the form of columns A = (q 1 ,q 2 ,…,q mn); Step 2, after column permutation, reorganize into A = (BN), where B is a reversible matrix; Step 3, find the column numbers of N in the matrix A, and form these column numbers into a set R; Step 4, perform the same column permutation as A on both vectors p and x (the columns here are scalars) and reorganize into p = (p B ,p N ) and x=(x B ,x N ), for example, suppose A=(q 1 ,q 2 ,q 3 ,q 4 ,q 5 ,q 6 ), p=(p 1 ,p 2 ,p 3 ,p 4 ,p 5 ,p 6 ), x=(x 1 ,x 2 ,x 3 ,x 4 ,x 5 ,x 6 ), if A is reorganized into A = (BN) after column permutation in the second step, where B = (q 1 ,q 3 ,q 5 ), N=(q 2 ,q 4 ,q 6 ), then p and x are swapped and reorganized into p = (p B ,p N ) and x=(x B ,x N ), where p B =(p 1 ,p 3 ,p 5 ) N =(p 2 ,p 4 ,p 6 ),x B =(x 1 ,x 3 ,x 5 ), x N =(x 2 ,x 4 ,x 6 ).

[0038] S3: Construct discriminator Δ: Calculate p for each element j in the set R described in S2 B B -1 q j-p j , let the value p corresponding to the kth element among these calculated values B B -1 q k -p k Maximum, let the discriminator Δ=p B B -1 q k -p k , if Δ≤0, then the best delivery strategy is x=(x B ,x N ), where x B =B -1 b,x N =0, step three ends; otherwise, go to the next step.

[0039] S4: Update the discriminator: for k described in S3, record x' B =B -1 q k x k , remember x B (i) and x' B (i) are x B and x' B The ith element of , calculate x for all i B (i) / x' B (i) Among these calculated values, let the rth value x B (r) / x' B (r) is the largest, then find x B The rth component in, for example, x h ; Then change column q in B k Replace q h , get the updated B, and go to S3.

[0040] Until step 3 is completed, the optimal delivery strategy x=(x B ,x N ), where x B =B -1 b,x N =0, that is, the shared bicycle company Ci deploys x to the demand location Dj ij A shared bicycle, here x ij Get the best delivery strategy for the element x.

Claims

1. A method for deploying shared bicycles in cities with the best overall benefits, characterized by the following steps: Step 1: Collecting the cost data of a shared bicycle company deploying a shared bicycle to a demand location; Step 2: Establishing a deployment model that coordinates overall benefits; Step 3: Constructing a deployment strategy based on the deployment model that coordinates overall benefits.

2. The method for placing shared bicycles in cities with the best global benefits according to claim 1, characterized in that: Step 2: Establish a delivery model that coordinates overall benefits: Among them, p ij is the cost of a shared bicycle company Ci (i = 1, 2, ..., m) to deploy a shared bicycle to the demand location Dj (j = 1, 2, ..., n), x ij is the number of shared bicycles that company Ci plans to deploy to demand location Dj, c i is the number of shared bicycles owned by the shared bicycle company Ci (i=1,2,…,m), d j is the demand for shared bicycles at the demand location Dj (j=1,2,…,n); Step 3: Based on the delivery model that takes into account the overall benefits, the methods for constructing delivery strategies include: 1) Model matrixing: Write the overall benefit delivery model established in step 2 into a matrix form: min px in, p=(p 11 ,p 12 ,…,p 1n ,p 21 ,p 22 ,…,p 2n ,…,p m1 ,p m2 ,…,p mn ), x=(x 11 ,x 12 ,…,x 1n ,x 21 ,x 22 ,…,x 2n …,x m1 ,x m2 ,…,x mn ) T , E is an n-dimensional row vector whose components are all 1, I is an n-order identity matrix, b=(c1,c2,…,c m ,d1,d2,…,d n ) T , T Represents the transpose of a vector; 2) Balance matrix reversibility reorganization: Write the balance matrix A in column form A = (q1, q2, ..., q mn ) and reorganize into A = (BN) by column transposition so that B is a reversible matrix, and the set of column numbers of N in matrix A is denoted as R; p and x are both reorganized into p = (p B ,p N ) and x=(x B ,x N ); 3) Construct the discriminator Δ: Calculate p for each element j in the set R described in 2) B B -1 q j -p j , among these calculated values, let the value p corresponding to the kth element B B -1 q k -p k Maximum, let the discriminator Δ=p B B -1 q k -p k , if Δ≤0, then the best delivery strategy is x=(x B ,x N ), where x B =B -1 b,x N =0, step 3 ends; otherwise, go to the next step; 4) Update the discriminator: for k mentioned in 3), record x' B =B -1 q k x k , remember x B (i) and x' B (i) are x B and x' B The ith element of , calculate x for all i B (i) / x' B (i) Among these calculated values, let the rth value x B (r) / x' B (r) is the largest, then find x B The rth component in, for example, x h ; Then change column q in B k Replace q h , get the updated B, go to 3).

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