Abstract
In the vehicle routing problem (VRP), it is usually difficult to confederate the cargo and arrange vehicles path. Due to performance reasons, the traditional shortest path algorithm can not be applied to the large scale of VRP. On the basis of the VRP mathematical model, this paper constructs a mixed climbing particle swarm algorithms to solve the problem. First, through coding, the VRP problem is divided into two sub-problems: task allocation and single vehicle path optimization. Particle swarm algorithm is in charge of controlling the overall situation and allocating task, while hill-climbing algorithm is responsible for calculating the vehicle path optimization (fitness). Finally, by performing experiments in MATLAB programming and comparison of the operational results of the matrix method and genetic algorithm, the algorithm is shown to be feasible in solving VRP and have higher practicability.
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