Kazım ErdoǧduKorhan Karabulut2025-10-06202214753995, 096960160969-60161475-399510.1111/itor.13044https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112478667&doi=10.1111%2Fitor.13044&partnerID=40&md5=97732fdab3c4c2757c48fb2767ab8cd6https://gcris.yasar.edu.tr/handle/123456789/8725The 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. © 2021 Elsevier B.V. All rights reserved.EnglishAdaptive Large Neighborhood Algorithm, Evolutionary Algorithms, Green Vehicle Routing Problem, Multiobjective Algorithms, Multiobjective Optimization Problem, Heuristic Algorithms, Heuristic Methods, Optimization, Vehicles, Adaptive Large Neighborhood Searches, Bench-mark Problems, Environmental Issues, Local Search Heuristics, Number Of Vehicles, Solution Methods, Vehicle Routing Problem, Vehicle Routing Problems, Vehicle RoutingHeuristic algorithms, Heuristic methods, Optimization, Vehicles, Adaptive large neighborhood searches, Bench-mark problems, Environmental issues, Local search heuristics, Number of vehicles, Solution methods, Vehicle routing problem, Vehicle Routing Problems, Vehicle routingArticle