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1. Introduction
Vehicle routing problem (VRP) is one of combinatorial optimization problems and VRP can be turned into other application problems; for example, Chen and Wang have turned VRP into tour planning problem [1]. A typical VRP can be described as follows: a warehouse that offers services to different positions of customers at the lowest cost path planning. It has real economic significance in many fields, such as transportation scheduling, routing, railway transportation, and other practical problems. Currently, heuristic algorithm is the main method for solving vehicle routing problem. Heuristic algorithm can be divided into simple heuristic algorithm, two-phase heuristic algorithm, and artificial intelligence methods.
Vehicle routing problem has successfully applied in many areas, such as Li et al. [2] and Malekly et al. [3]. They solve the uncertain and ambiguous problem in vehicle routing problem using fuzzy set theories. Toth and Vigo [4] considered VRP as a significant part in logistic handing and grouped the methods that have been found to solve the problem of VRP. Kim et al. [5] divided the waste collection business into different areas and proposed methods to solve these problems in VRP. Many researchers have proposed heuristics or metaheuristics algorithm for efficiently solving the vehicle routing problem. Semet and Taillard [6] designed the taboo algorithm considering time window and different types of vehicles, which mainly used methods to generate the initial solution, then optimize the initial solution with taboo search algorithm. It is a local neighborhood search for an extension. Cordeau and Laporte [7] studied simulated annealing algorithm for the VRP, they proposed a simulated annealing method which is suitable for solving the vehicle routing problem and shows the advantage of accuracy and the speed of search convergence. Genetic algorithm is good for solving combinatorial optimization problems. Niazy and Badr [8] and Zulvia et al. [9] use genetic algorithm (GA) encoding to solve VRP problem....