Journal
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
Volume 29, Issue 3, Pages 1602-1626Publisher
WILEY
DOI: 10.1111/itor.13044
Keywords
green vehicle routing problem; multiobjective optimization problem; adaptive large neighborhood algorithm; evolutionary algorithms; multiobjective algorithms
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The green vehicle routing problem has become a popular research area due to increasing global environmental concerns. Studies suggest that optimizing vehicle routes and reducing fuel consumption can help mitigate the negative impact of pollution on human health.
The green vehicle routing problem (GVRP) is a variant of the vehicle routing problem (VRP), which increasingly attracts many researchers in recent years due to the growing global environmental issues. As the transportation of the products grows, the number of vehicles in fleets and the pollutants caused by these vehicles also grow, which in turn negatively affects human health. In this paper, a biobjective GVRP was studied. The two objectives are minimizing the total distance and minimizing the total fuel consumption of all vehicle routes. As a solution method, an adaptive large neighborhood search was hybridized with two new local search heuristics. The proposed method was applied to two well-known benchmark problem sets for VRPs and new approximate Pareto fronts were obtained for these benchmark sets.
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