Vehicle routing problem using clustering algorithm by maximum neural networks

N. Yoshiike, Yoshiyasu Takefuji

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

3 Citations (Scopus)

Abstract

The vehicle routing problem (VRP) is one of the well known optimization problems. It is used to minimize the total length of all routes of vehicles where each of the vehicle has a capacity constraint respectively. This paper proposes a self-organization neural network model for obtaining the best solution for VRP. Our method consists of two phases. In the first phase, the customers are grouped to several delivery areas for vehicles assignment by Maximum Neuron model. In the second phase, the TSP in each area is solved by Elastic net model proposed by Andrew et. al. The clustering algorithm used in the first phase is a Maximum Neuron model. Maximum Neuron model is one of the neural networks proposed by Hopfield that can minimize a cost function considering various constraints. In the second phase, Elastic net model is used to solve the problem and it can obtain good solutions of TSP. Our method improves the precision of solution, and can be extended for big size problem. Our simulation result shows that Maximum Neuron model can achieve better solutions than other methods in certain conditions.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1109-1113
Number of pages5
Volume2
ISBN (Electronic)0780354893, 9780780354890
DOIs
Publication statusPublished - 1999 Jan 1
Event2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 - Honolulu, United States
Duration: 1999 Jul 101999 Jul 15

Other

Other2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
CountryUnited States
CityHonolulu
Period99/7/1099/7/15

Fingerprint

Vehicle routing
Clustering algorithms
Neural networks
Neurons
Cost functions

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Materials Science (miscellaneous)

Cite this

Yoshiike, N., & Takefuji, Y. (1999). Vehicle routing problem using clustering algorithm by maximum neural networks. In Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 (Vol. 2, pp. 1109-1113). [791534] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPMM.1999.791534

Vehicle routing problem using clustering algorithm by maximum neural networks. / Yoshiike, N.; Takefuji, Yoshiyasu.

Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 1999. p. 1109-1113 791534.

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

Yoshiike, N & Takefuji, Y 1999, Vehicle routing problem using clustering algorithm by maximum neural networks. in Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. vol. 2, 791534, Institute of Electrical and Electronics Engineers Inc., pp. 1109-1113, 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999, Honolulu, United States, 99/7/10. https://doi.org/10.1109/IPMM.1999.791534
Yoshiike N, Takefuji Y. Vehicle routing problem using clustering algorithm by maximum neural networks. In Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. Vol. 2. Institute of Electrical and Electronics Engineers Inc. 1999. p. 1109-1113. 791534 https://doi.org/10.1109/IPMM.1999.791534
Yoshiike, N. ; Takefuji, Yoshiyasu. / Vehicle routing problem using clustering algorithm by maximum neural networks. Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 1999. pp. 1109-1113
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