摘要
为提高自动化码头核心设备的装卸效率,需要对核心设备进行有效管理,由此大多文献建立了自动化码头核心资源的集成调度模型。针对自动化码头三种核心设备的调度模型,提出了一种更精确的遗传算法来解决这个问题。首先采用改进型单点交叉算子和双变异算子对遗传算法进行改进,进而利用改进的遗传算法对问题进行求解。为了评估改进后的遗传算法性能,随后设计两组不同规模的数值仿真,与采用CPLEX求解得到的下界进行比较,可知两者之间的差值平均为1.8%,最大为3.8%,最小为0.6%,且在实际当中遗传算法的计算机运算时间处于可接受范围内。结果表明,改进后的遗传算法能够找到高质量的近似最优解。
To improve the loading and unloading efficiency of the key equipment of the automatic terminal, the key equipment should be managed effectively, so the model of integrated scheduling of the key resources of the auto- matic terminal was established as in many literatures. A more accurate genetic algorithm was proposed to solve the scheduling problem of three kinds of core equipment. The improved single point crossover operator and double mutation operator werr used to improve the genetic algorithm and then to solve the problem. In order to evaluate the performance of genetic algorithm, we designed two different scale numerical experiment, and compared with the lower bound obtained by CPLEX, the average difference between the two is I. 8%, the maximum is 3.8%, the minimum is 0.6%, and the computer operation time of the genetic algorithm is in the acceptable range. The results show that the improved genetic algorithm can find the near optimal solution with high quality.
出处
《计算机仿真》
北大核心
2018年第3期381-384,421,共5页
Computer Simulation
基金
上海市教委科研创新项目基金(15ZZ078)
浦江人才计划(16PJC043)
2016年研究生学术新人培育项目(YXR2016074)
关键词
自动化码头
核心设备
集成调度
改进的遗传算法
Automated terminal
Key equipments
Integrated scheduling
Modified genetic algorithm
