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A recent review of solution approaches for green vehicle routing problem and its variants

元启发式 计算机科学 数学优化 车辆路径问题 并行元启发式 整数规划 MATLAB语言 布线(电子设计自动化) 算法 数学 元优化 计算机网络 操作系统
作者
Annisa Kesy Garside,Noor Azurati Ahmad,Mohd Nabil Muhtazaruddin
出处
期刊:Operations Research Perspectives [Elsevier BV]
卷期号:12: 100303-100303 被引量:8
标识
DOI:10.1016/j.orp.2024.100303
摘要

The green vehicle routing problem (GVRP) has been a prominent topic in the literature on logistics and transportation, leading to extensive research and previous review studies covering various aspects. Operations research has seen the development of various exact and approximation approaches for different extensions of the GVRP. This paper presents an up-to-date and thorough review of GVRP literature spanning from 2016 to 2023, encompassing 458 papers. significant contribution lies in the updated solution approaches and algorithms applied to both single-objective and multi-objective GVRP. Notably, 92.58% of the papers introduced a mathematical model for GVRP, with many researchers adopting mixed integer linear programming as the preferred modeling approach. The findings indicate that both metaheuristics and hybrid are the most employed solution approaches for addressing single-objective GVRP. Among hybrid approaches, the combination of metaheuristics-metaheuristics is particularly favored by GVRP researchers. Furthermore, large neighborhood search (LNS) and its variants (especially adaptive large neighborhood search) emerges as the most widely adopted algorithm in single-objective GVRP. These algorithms are proposed within both metaheuristic and hybrid approaches, where A-/LNS is often combined with other algorithms. Conversely, metaheuristics are predominant in addressing multi-objective GVRP, with NSGA-II being the most frequently proposed algorithm. Researchers frequently utilize GAMS and CPLEX as optimization modeling software and solvers. Furthermore, MATLAB is a commonly employed programming language for implementing proposed algorithms.
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