A hybrid meta heuristic algorithm proposal and an application for the multi depot simultaneous pickup and delivery green vehicle routing problem

This study focuses on the green vehicle routing problem, which is one of the fundamental topics in green logistics. With the green vehicle routing problem, businesses aim to minimize the damage to the environment while continuing their routing activities. Within the scope of this thesis, the multi-depot simultaneous pick-up and delivery green vehicle routing problem for a company operating in the mineral oil sector with warehouses in Antalya and Konya is discussed. The mixed integer mathematical model was developed to solve this problem, aiming to determine the most suitable routes for vehicles and minimizing the sum of fuel consumption and variable costs while determining these routes. The mathematical model takes into account various parameters such as vehicle speed, fuel consumption rate, type of fuel used by the vehicle, customer service times, pickup requests, and distribution requests. Two different scenarios are considered for small and large problems, considering the situation of the business. For the problems expressed, a solution was sought with the exact solution in the GAMS software, the nearest neighbor algorithm adapted to the problem coded in MATLAB, and the hybrid algorithm written in MATLAB, which includes the nearest neighbor, tabu search, simulated annealing, and local search algorithms. For small problems, the hybrid algorithm gives optimal or approximate solution. Since the GAMS software did not yield results in the large problem, the proposed hybrid algorithm was compared with the nearest neighbor algorithm adapted to the problem. The proposed hybrid algorithm provided better results in reasonable time. The mathematical model developed for the problem in this study, the fact that the technical features of the tools used in the problem are not the same, and the proposed hybrid algorithm reveal the difference of the study.