Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics

In this study, we consider a canonical vehicle routing problem (VRP) in the cold chain logistic system, where three special constraints are included, i.e., the dispatching time windows for each customer, different types of vehicles, and different energy consumptions and capacities for each vehicle. The objective is to minimize the total cost including the fixed cost and the energy consumptions. An improved artificial fish swarm (IAFS) algorithm is proposed, where a special encoding approach is designed to consider the problem feature with different type of vehicles. Then, improved preying and following heuristics are developed to perform the exploitation and exploration tasks. A novel customer satisfaction heuristic is embedded in the proposed algorithm, which makes the problem close to the reality. To further improve the performance of the algorithm, a right-shifting heuristic is designed to increase the customer satisfaction without increasing the energy consumption. An initialization heuristic based on the canonical Put Forward Insertion Heuristics (PFIH) is proposed to generate initial solutions with better performance. Finally, a set of realistic instances is generated to test the performance of the proposed algorithm, and after detailed experimental comparisons, the competitive performance of the proposed algorithm is verified. (C) 2020 Elsevier B.V. All rights reserved.