A hybrid complementary metaheuristic for VRPTW with product classification and pickup-delivery constraints

Abstract

With the emphasis of the exhaust gas emission of the transportation vehicles, the mode of picking up and delivering products simultaneously has become a challenging issue in the vehicle routing problem (VRP). To remedy this issue, we investigate a special VRP with realistic constraints including product classification, pickup-delivery, and time window (PC-VRPSPDTW). Then, a hybrid algorithm combining tabu search and artificial immune algorithm (TS-AIA) is proposed. In the proposed algorithm, the earliest time and residual capacity (ETRC) heuristic is designed to generate the initial population. Then, two metaheuristics including variable neighborhood search and large neighborhood search are cooperated to balance the exploration and exploitation abilities. Besides, a new crossover operator is designed to increase the population diversity. Finally, a series of comparative experiments on the extension version of the Solomon’s benchmarks are performed to verify the effectiveness of the proposed algorithm.