Research on Vehicle Routing Genetic Algorithm from the Perspective of Customer Level Division
In response to the problems of low vehicle load factor,long vehicle path solving time and high vehicle delivery cost in current vehicle path planning algorithms,this paper designs a vehicle path genetic algorithm solution process that considers customer level division.On the basis of describing vehicle routing related problems and functions,relevant assumptions and constraints are given,the objective function is determined,and customer level division is considered.Then,a time window vehicle routing model is constructed.Using genetic algorithm,an initial population is generated through chromosome encoding,and then the optimal solution is output through selection,crossover,and mutation to solve the time window vehicle path.The experimental results show that this method can effectively improve the vehicle's full load rate,shorten the solution time,and reduce delivery costs.
vehicle routing problemcustomer level divisiongenetic algorithmfitness functionmutation probability
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维普
