Distribution center site selection method based on bacterial foraging optimization algorithm
A distribution center and optimization algorithm technology, applied in the field of logistics, can solve the problems of the final site selection result, which has a great influence, easy to fall into local optimum, and easy to mature prematurely.
Active Publication Date: 2018-07-03
HEFEI UNIV OF TECH
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Problems solved by technology
The tabu search algorithm is the earliest algorithm applied to the problem of site selection. It can avoid falling into local optimum by establishing a tabu table, but its initial solution has a great influence on the quality of the final site selection result; the genetic algorithm solves it by simulating the natural evolution process , but it is easy to be premature; although the particle swarm optimization algorithm has a high solution efficiency, it is easy to fall into a local optimum; the ant colony algorithm solves the problem through the foraging behavior of ants, but it also has the disadvantage of being easy to fall into a local optimum
Bacterial foraging optimization algorithm, as a kind of swarm intelligence optimization algorithm, also has the disadvantage of being easy to fall into local optimum
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[0090] In this embodiment, a distribution center site selection method based on bacteria foraging optimization algorithm is carried out in the following steps:
[0091] Step 1. Obtain the set of historical delivery addresses of the target city, recorded as N={N 1 ,N 2 ,...,N i ,...,N n}, N i Indicates the i-th historical delivery address, i=1,2,...,n; construct the distribution center of the target city, recorded as M={M 1 , M 2 ,...,M j ,...,M m}, M j Indicates the jth distribution center, j=1,2,...,m; constructing the distribution center construction cost vector F=[f 1 ,f 2 ,..., f j ,..., f m ], f j >0 means the jth distribution center M j The construction cost of ; construct the transportation cost matrix C of the target city = (c ij ) m×n , c ij >0 means the jth distribution center M j To the i-th historical delivery address N i transportation costs between
[0092] Step 2. Construct the location selection model of the distribution center. The location ...
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The invention discloses a distribution center site selection method based on a bacterial foraging optimization algorithm. The method comprises the steps of 1) obtaining a distribution center and a historical distribution address set of a target city; 2) constructing a distribution center site selection model; and 3) implementing a bacterial foraging optimization algorithm. The method of the invention can perform modeling by using historical distribution addresses and a candidate distribution center and is more in line with distribution center site selection conditions in the presence of large-scale historical distribution addresses in reality, so that the site selection and the distribution can be combined to improve the accuracy of the site selection of the distribution center, reduce thedistribution cost, improve the timeliness of distribution, and improve customer satisfaction.
Description
technical field [0001] The invention relates to the technical field of logistics, in particular to a distribution center site selection method based on a bacterial foraging optimization algorithm. Background technique [0002] The problem of location selection has a long history and exists in all aspects of life, such as the location of factories, logistics distribution centers, and public service facilities. With the development of e-commerce, logistics distribution has become an indispensable part of supply chain management, and the location selection of distribution centers is becoming more and more important. A better distribution center site selection will not only consider the cost of building the distribution center, but also consider the distribution costs of the distribution center and the historical distribution address, so as to improve the logistics transportation efficiency in the supply chain, reduce transportation costs, and Improve customer satisfaction, and...
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Login to View More IPC IPC(8): G06Q10/04G06Q10/08G06N3/00
CPCG06N3/006G06Q10/04G06Q10/08355
Inventor 凌海峰孙舫刘业政姜元春孙见山孙春华陈夏雨傅怡
Owner HEFEI UNIV OF TECH