Research on an improved genetic algorithm for logistics distribution path optimization

Xue Sun, Chih Kuang Yang, kai-cheng wei, Chao-Chin Wu, Liang-Rui Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Logistics distribution path optimization as an NP-hard problem is one of the important problems in logistics. Many intelligent algorithms are considered to be used to solve such problems. In this paper, an improved genetic algorithm is proposed for solving Travelling Salesman Problem (TSP), a kind of classical logistics distribution path optimization problem. The method uses island model genetic algorithm to formulate rules that are more suitable for TSP, through applying greedy algorithm in the generation of initial population, modifying the selection method and discussing different migration strategies, the computation time of solving the problem is shorten, the calculation efficiency is improved, and the probability of falling into the local optimal solution is reduced. Finally, experiments are conducted to discuss the effectiveness of our method.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages282-286
Number of pages5
ISBN (Print)9781450366045
DOIs
Publication statusPublished - 2018 Jan 1
Event2018 Asia-Pacific Conference on Intelligent Medical, APCIM 2018 and 7th International Conference on Transportation and Traffic Engineering, ICTTE 2018 - Beijing, China
Duration: 2018 Dec 212018 Dec 23

Publication series

NameACM International Conference Proceeding Series
VolumePart F148260

Conference

Conference2018 Asia-Pacific Conference on Intelligent Medical, APCIM 2018 and 7th International Conference on Transportation and Traffic Engineering, ICTTE 2018
CountryChina
CityBeijing
Period18-12-2118-12-23

Fingerprint

Logistics
Traveling salesman problem
Genetic algorithms
Computational complexity
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Cite this

Sun, X., Yang, C. K., wei, K., Wu, C-C., & Chen, L-R. (2018). Research on an improved genetic algorithm for logistics distribution path optimization. In ACM International Conference Proceeding Series (pp. 282-286). (ACM International Conference Proceeding Series; Vol. Part F148260). Association for Computing Machinery. https://doi.org/10.1145/3321619.3321674
Sun, Xue ; Yang, Chih Kuang ; wei, kai-cheng ; Wu, Chao-Chin ; Chen, Liang-Rui. / Research on an improved genetic algorithm for logistics distribution path optimization. ACM International Conference Proceeding Series. Association for Computing Machinery, 2018. pp. 282-286 (ACM International Conference Proceeding Series).
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abstract = "Logistics distribution path optimization as an NP-hard problem is one of the important problems in logistics. Many intelligent algorithms are considered to be used to solve such problems. In this paper, an improved genetic algorithm is proposed for solving Travelling Salesman Problem (TSP), a kind of classical logistics distribution path optimization problem. The method uses island model genetic algorithm to formulate rules that are more suitable for TSP, through applying greedy algorithm in the generation of initial population, modifying the selection method and discussing different migration strategies, the computation time of solving the problem is shorten, the calculation efficiency is improved, and the probability of falling into the local optimal solution is reduced. Finally, experiments are conducted to discuss the effectiveness of our method.",
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Sun, X, Yang, CK, wei, K, Wu, C-C & Chen, L-R 2018, Research on an improved genetic algorithm for logistics distribution path optimization. in ACM International Conference Proceeding Series. ACM International Conference Proceeding Series, vol. Part F148260, Association for Computing Machinery, pp. 282-286, 2018 Asia-Pacific Conference on Intelligent Medical, APCIM 2018 and 7th International Conference on Transportation and Traffic Engineering, ICTTE 2018, Beijing, China, 18-12-21. https://doi.org/10.1145/3321619.3321674

Research on an improved genetic algorithm for logistics distribution path optimization. / Sun, Xue; Yang, Chih Kuang; wei, kai-cheng; Wu, Chao-Chin; Chen, Liang-Rui.

ACM International Conference Proceeding Series. Association for Computing Machinery, 2018. p. 282-286 (ACM International Conference Proceeding Series; Vol. Part F148260).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Sun X, Yang CK, wei K, Wu C-C, Chen L-R. Research on an improved genetic algorithm for logistics distribution path optimization. In ACM International Conference Proceeding Series. Association for Computing Machinery. 2018. p. 282-286. (ACM International Conference Proceeding Series). https://doi.org/10.1145/3321619.3321674