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A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon Vehicle Routing Problem

  • Xiaoning Shen
  • , Jiaqi Lu
  • , Xuan You
  • , Liyan Song*
  • , Zhongpei Ge
  • *Corresponding author for this work
  • Nanjing University of Information Science & Technology
  • The Research Institute of Trustworthy Autonomous Systems
  • Southern University of Science and Technology

Research output: Contribution to journalArticlepeer-review

Abstract

A constrained multi-objective optimization model for the low-carbon vehicle routing problem (VRP) is established. A carbon emission measurement method considering various practical factors is introduced. It minimizes both the total carbon emissions and the longest time consumed by the sub-tours, subject to the limited number of available vehicles. According to the characteristics of the model, a region enhanced discrete multi-objective fireworks algorithm is proposed. A partial mapping explosion operator, a hybrid mutation for adjusting the sub-tours, and an objective-driven extending search are designed, which aim to improve the convergence, diversity, and spread of the non-dominated solutions produced by the algorithm, respectively. Nine low-carbon VRP instances with different scales are used to verify the effectiveness of the new strategies. Furthermore, comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon VRP. It provides a promising scalability to the problem size.

Original languageEnglish
Pages (from-to)142-155
Number of pages14
JournalComplex System Modeling and Simulation
Volume2
Issue number2
DOIs
StatePublished - 1 Jun 2022
Externally publishedYes

Keywords

  • carbon emission
  • fireworks algorithm
  • multi-objective optimization
  • region enhanced
  • vehicle routing problem

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