Multi-objective vehicle routing problem with time windows based on improved simulated annealing algorithm

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Abstract
Aiming at the vehicle routing problem with time window constraints, this paper discusses the vehicle routing optimization problem among multiple warehouses, multiple products and multiple customers. In this paper, a multi-objective model of vehicle path optimization based on the improved simulated annealing algorithm is established by adding memory function and setting monotonous heating up and other real-time optimization strategies. The optimization objectives include total transportation cost, total driving distance and total driving time. In order to prove the effectiveness of the proposed model, the optimization results of standard genetic algorithm, random search and the algorithm in this paper are compared on the randomly generated dataset. The simulation results show that the algorithm designed in this paper is fast and efficient in all four cases.