摘要
研究了考虑车辆数和总成本情况下的软时间窗车辆路线问题的多目标规划问题。提出了一种改进的遗传算法,在算法中利用适应度函数解决了两个目标之间的平衡问题。通过修改交换算子,不仅增加了算法的搜索能力,还去掉了种群差异性的限制。通过实例验证说明该算法能有效地解决软时间窗车辆路线问题,为实际应用提供有力的决策支持。
The paper studies the multi-objective programming of the vehicle routing problem with soft time window （VRPSTW） that considers both number of vehicles and total cost and proposes an improved genetic algorithm for its solution where fitness function is used to reach the balance between two objectives and crossover operators are modified to increase the search capacity of the algorithm and to drop the limit on population diversity. Finally a case study is carried out to verify the effectiveness of the algorithm in the solution of VRPSTW.
出处
《物流技术》
2010年第9期78-79,共2页
Logistics Technology
