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中文摘要：
为提升自动化集装箱码头的作业效率,减轻码头吞吐量增大带来的交通问题,降低自动化导引小车（Automated Guided Vehicle,AGV）的空载率,在自动化集装箱码头应用可以同时搬运不止一个集装箱的多载AGV,建立多载AGV调度问题的混合整数线性规划（Mixed-Integer Linear Programming,MILP）模型,应用遗传算法进行求解.借助算例,对比遗传算法与MILP算法的求解效果,分析交叉概率和变异概率对遗传算法的影响,比较多载AGV与单载AGV的作业时间,验证遗传算法的可靠性.该方法表明,遗传算法不仅求解效率高,而且对MILP算法不适用的大、中型多载AGV调度问题,也能给出值得信赖的近似最优解.
英文摘要：
In order to improve work efficiency of automatic container terminals,relieve traffic problem caused by increased handling capacity,and lower empty load ratio of Automated Guided Vehicles（ AGVs）,the multi-load AGVs that can move more than one container at the same time are used in automated container terminals,a Mixed-Integer Linear Programming（ MILP） model is established for the multi-load AGV scheduling issue,and the genetic algorithm is applied to solve the model. Through examples,the solving effects of the genetic algorithm and the MILP algorithm are compared,the impacts of crossover probability and mutation probability on the genetic algorithm are analyzed,the working times between multi-load AGVs and single-load AGVs are compared,and the reliability of the genetic algorithm is verified. The method indicates that the genetic algorithm is not only effective in solving the issues but also capable of giving the reliable and approximate optimal solutions to large- and medium-scaled AGV scheduling issues to which the MILP algorithm is inappropriate.
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