易腐产品运输调度问题的优化①

摘要

The perishable products go bad easily in transportational process and have the trait of timeliness and incident among goods. This paper proposed a mathematical model of Incident Vehicle Route Problem with Time Window (IVRPTW) to consider production distribution for perishable products.And adapt the Immune Clonal Selection Algorithm(ICSA) to solve this complex problem. On the basis of modeling and simulating examples of this problem, it is shown that the programming model and algorithm are reasonable and efficient.Experiment result also shows the immune clonal selection algorithm can find the optimal or nearly optimal solution effectively compared with the genetic algorithm.%　　针对易腐产品在运输过程中容易变质，具有时效性和货物关联性的特点，构建一种带软时间窗的关联运输调度问题的数学模型来考虑易腐产品的配送，并采用免疫克隆选择算法求解这个复杂问题。通过对该问题进行分析建模和数值求解，说明了该模型和算法的合理性和有效性。与遗传算法相比较，免疫克隆选择算法能更有效地解决关联运输调度问题。