Abstrato

A fleet size and mix vehicle routing problem with quantity discounts for outsourcing

Yang-Yang Hao, Sha Tao, Zhi-Hua Hu

In view of the fleet size and mix vehicle routing problem with quantity discounts for outsourcing, a non-linear programming model is established; and an evolutionary algorithm based on the shortest path encoding approach is designed to solve the model by minimize the variable costs and outsourcing costs. Through experimental analysis, it is shown that: the mutation probability and population size affects the optimal fitness defined by total costs; the higher mutation probability and bigger population size would quicken the convergence speed and quality of the evolutionary algorithm; the bigger population size would cost more computational time; other parameters impose no significant effect on experimental results. Based on these results, optimal parameters for the algorithm are determined. By a case, the performance and the effects of the algorithm are demonstrated.