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 language | English |
|---|---|
| Article number | 101463 |
| Journal | Swarm and Evolutionary Computation |
| Volume | 85 |
| Online published | 9 Jan 2024 |
| DOIs | |
| Publication status | Published - Mar 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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