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Author:

Li, Shilong (Li, Shilong.) | Du, Shengli (Du, Shengli.) | Wu, Di (Wu, Di.) | Gao, Yongfeng (Gao, Yongfeng.)

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EI Scopus

Abstract:

This paper is concerned with the routing problem of a mixed vehicle fleet composed by both electric and conventional vehicles. A bi-objective model with the aim of minimizing carbon emissions and maximising customer satisfaction is established. To further tackle the challenges posed by the distinct constraints of electric and conventional vehicles, a partial variable-length coding method is introduced to facilitate chromosome generation in the model. Then, a novel NSGA-II including the above designed coding method is proposed for solving the optimization problem. By comparing the experiments results of solving separate single-objective optimization and the two conflict optimization objectives simultaneously, it is verified that the proposed encoding approach and algorithm is effective. The results suggest that the bi-objective model is well-established, demonstrating the anticipated conflict between the two objectives. Additionally, the partial variable-length coding method is shown to be effective in achieving chromosome generation tasks. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

Keyword:

Vehicle routing Fleet operations Customer satisfaction

Author Community:

  • [ 1 ] [Li, Shilong]Beijing University of Technology, School of Artificial Intelligence and Automation, Beijing; 100124, China
  • [ 2 ] [Li, Shilong]Beijing Laboratory of Smart Environmental Protection, Beijing; 100124, China
  • [ 3 ] [Du, Shengli]Beijing University of Technology, School of Artificial Intelligence and Automation, Beijing; 100124, China
  • [ 4 ] [Du, Shengli]Beijing Laboratory of Smart Environmental Protection, Beijing; 100124, China
  • [ 5 ] [Wu, Di]Dalian University of Technology, School of Control Science and Control Engineering, Dalian; 116024, China
  • [ 6 ] [Gao, Yongfeng]Dalian University of Technology, School of Control Science and Control Engineering, Dalian; 116024, China

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Source :

ISSN: 1934-1768

Year: 2024

Page: 6596-6601

Language: English

Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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