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MOEA/D with customized replacement neighborhood and dynamic resource allocation for solving 3L-SDHVRP

  • Han Li
  • , Genghui Li
  • , Qiaoyong Jiang
  • , Jiashu Wang
  • , Zhenkun Wang*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Split delivery heterogeneous vehicle routing problem with three-dimensional loading (3L-SDHVRP) is a critical issue in manufacturing logistics. Current mainstream research formulates this problem as a single objective optimization problem, which fails to reveal the relationship among multiple conflicting objectives and cannot provide various trade-off solutions for decision-makers in real-world logistics scenarios. This paper concentrates on a multi-objective 3L-SDHVRP and proposes a multi-objective evolutionary algorithm based on decomposition with customized replacement neighborhood and dynamic resource allocation (called MOEA/D-RD) to deal with it. The numerical experiments on the dataset from the 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2021) show the superior performance of the proposed method over some state-of-the-art ones. The source code of MOEA/D-RD is available at https://github.com/CIAM-Group/EvolutionaryAlgorithm_Codes/tree/main/MOEAD-RD. © 2024 Elsevier B.V.
Original languageEnglish
Article number101463
JournalSwarm and Evolutionary Computation
Volume85
Online published9 Jan 2024
DOIs
Publication statusPublished - Mar 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • Dynamic resource allocation
  • Evolutionary algorithm
  • Multi-objective evolutionary algorithm based on decomposition
  • Multi-objective optimization
  • Three-dimensional loading and vehicle routing problem

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