摘要
在实际运输过程中,一些客户会根据自己的需求情况预先规定货物的送达时间,即时间窗约束。本文所研究的时间窗主要是软时间窗,即当货物的送达时间早于客户规定的最早运输时间时,承运方需要支付相应的库存费用;当货物的送达时间迟于客户规定的最迟运输时间,则承运方将根据合同规定支付相应的惩罚费用。本文在以往研究的基础上,提出一个带有时间约束的双目标运输成本模型。该模型在考虑时间窗约束条件下包含两个目标:一个是达到运输车辆数最低,另一个是追求运输成本最低。本文将通过一个改进的遗传算法和对该问题进行求解。最后,本文通过一个案例验证了该模型的准确性和可行性。
In the real practice of transportation, some customers will predefine the arrival time which is called time-window constraints. In this paper,the soft time-window constraints that specify the earliest and latest arrival times of customers are focused. If a customer is serviced before the earliest specified arrival time,extra inventory costs are incurred. If the customer is serviced after the latest arrival time, penalty costs must be paid. In this paper a bi-objective transportation cost model with time-window constraints is proposed. Both the total transportation cost and the required fleet size are minimized in this model, which also accounts for the given capacity limitations of each vehicle. This bi-objective optimization is solved by using a modified genetic algorithm approach. Finally, feasibility and validity of the model are illuminated through a case study.
出处
《中国管理科学》
CSSCI
北大核心
2016年第S1期137-144,共8页
Chinese Journal of Management Science
基金
北京市产学研联合培养研究生基地项目
中央高校基本科研业务专项资金项目(2016XS77)
关键词
运输成本
时间窗约束
遗传算法
Transportation cost
time-window constraints
genetic algorithm
