Multi-depot mixed fleet vehicle routing problem with mixed time windows

To solve the multi-depot mixed fleet vehicle routing problem with mixed time windows, by considering the multi-depot joint distribution, customers' mixed time windows, distribution transport capacity balance and the influence of vehicle loading capacity on fuel consumption comprehensively, an optimization model was established, which aimed to minimize the sum of vehicle dispatch costs, fuel consumption costs, electric vehicle energy costs and time penalty costs. A hybrid genetic algorithm with large neighborhood search was designed to solve the established model. This algorithm used the clustering method to generate the initial solution, and designed exchange and mutation operators based on the capacity balance strategy. To improve the depth search capability of the algorithm, the variable neighborhood search structure and the removal and insertion operators of the large neighborhood search algorithm were introduced. The effectiveness of the algorithm was verified by comparing and analyzing several groups of numerical examples. Furthermore, the impacts of transport capacity balance strategy and mixed time windows on distribution scheme formulation were analyzed. The study could enrich the related research on vehicle routing problem and provide the theoretical basis for logistics enterprises to optimize their distribution schemes. © 2023 CIMS. All rights reserved.