E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm
Based on the problem of e-commerce logistics and distribution network optimization, this paper summarizes the solution ideas and solutions proposed by domestic and foreign scholars and designs a method to optimize the B2C e-commerce logistics and distribution network by taking into account the speci...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5591811 |
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| author | Dong Yang Peijian Wu |
| author_facet | Dong Yang Peijian Wu |
| author_sort | Dong Yang |
| collection | DOAJ |
| description | Based on the problem of e-commerce logistics and distribution network optimization, this paper summarizes the solution ideas and solutions proposed by domestic and foreign scholars and designs a method to optimize the B2C e-commerce logistics and distribution network by taking into account the special traffic conditions in the city. The logistics network optimization model is established and solved by combining various methods. Taking into account the new target requirements constantly proposed in the modern logistics environment, the vehicle path problem under the generalized objective function is studied, and the multidimensional impact maximization problem in this type of problem is proposed and modeled. The problem follows from the path planning for emergency material delivery. Given locations, roads, and multiple classes of supplies in a map, each road allows vehicles to deliver each class of supplies with a certain probability. The goal of the problem is how to select a finite number of locations in the map as centers of supplies so that the number of locations that can be effectively covered by vehicle paths from them is maximized with the desired probability. For the first time, we used a hybrid genetic algorithm to optimize the e-commerce logistics path, and the optimized results are more reasonable than other algorithms. |
| format | Article |
| id | doaj-art-d9177d5b68e545f4ba07dab32e484610 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d9177d5b68e545f4ba07dab32e4846102025-02-03T05:57:50ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55918115591811E-Commerce Logistics Path Optimization Based on a Hybrid Genetic AlgorithmDong Yang0Peijian Wu1School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, Liaoning 116025, ChinaSchool of Business Administration, Anhui University of Finance and Economics, Bengbu, Anhui 233030, ChinaBased on the problem of e-commerce logistics and distribution network optimization, this paper summarizes the solution ideas and solutions proposed by domestic and foreign scholars and designs a method to optimize the B2C e-commerce logistics and distribution network by taking into account the special traffic conditions in the city. The logistics network optimization model is established and solved by combining various methods. Taking into account the new target requirements constantly proposed in the modern logistics environment, the vehicle path problem under the generalized objective function is studied, and the multidimensional impact maximization problem in this type of problem is proposed and modeled. The problem follows from the path planning for emergency material delivery. Given locations, roads, and multiple classes of supplies in a map, each road allows vehicles to deliver each class of supplies with a certain probability. The goal of the problem is how to select a finite number of locations in the map as centers of supplies so that the number of locations that can be effectively covered by vehicle paths from them is maximized with the desired probability. For the first time, we used a hybrid genetic algorithm to optimize the e-commerce logistics path, and the optimized results are more reasonable than other algorithms.http://dx.doi.org/10.1155/2021/5591811 |
| spellingShingle | Dong Yang Peijian Wu E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm Complexity |
| title | E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm |
| title_full | E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm |
| title_fullStr | E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm |
| title_full_unstemmed | E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm |
| title_short | E-Commerce Logistics Path Optimization Based on a Hybrid Genetic Algorithm |
| title_sort | e commerce logistics path optimization based on a hybrid genetic algorithm |
| url | http://dx.doi.org/10.1155/2021/5591811 |
| work_keys_str_mv | AT dongyang ecommercelogisticspathoptimizationbasedonahybridgeneticalgorithm AT peijianwu ecommercelogisticspathoptimizationbasedonahybridgeneticalgorithm |