Bi-objective Optimization with Partial Variable-length Coding Method for Mixed Fleet Vehicle Routing Problem

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...

Full description

Saved in:
Bibliographic Details
Published in:Chinese Control Conference pp. 6596 - 6601
Main Authors: Li, Shilong, Du, Shengli, Wu, Di, Gao, Yongfeng
Format: Conference Proceeding
Language:English
Published: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2024
Subjects:
Batteries
Carbon dioxide
Customer satisfaction
Encoding
Mixed Fleet Vehicle Routing Problem
NSGA-II
Optimization methods
Partial Variable-length Coding Method
Routing
Vehicle routing
ISSN:1934-1768
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1934-1768
DOI:10.23919/CCC63176.2024.10662585