摘要
在集装箱装卸作业问题中,以集装箱簇为作业单位,分两阶段分析集装箱在岸桥集卡间的调度方案,以集卡空驶率最小与移动距离最短为目标,建立了整数规划模型。针对上述模型,利用启发式算法与自适应遗传算法对问题进行分析求解。最后通过配置不同集卡数量,将其移动总距离以及空驶效率进行比较,并与禁忌搜索算法相对比。实验结果表明,启发式自适应遗传算法的计算结果在空驶率以及移动总距离最小问题上有更优的解决方案。
This paper focused on the question of loading and unloading of containers, and analyzed the yard truck scheduling in two stages, with considered the loading and unloading of containers. It developed a mixed integer programming model, where the objective was to minimize the rate of empty-loading and the total distance which was from sum overloading distance and empty-loading distance. And it used heuristic algorithm and adaptive genetic algorithm to solve the above model. Finally with heuristic-adaptive genetic algorithm and Tabu search algorithm, it computed the mathematical model deployed different quantity of yard trucks. The result from experiment case proves that the result of the H-AGA is better than that of Tabu search algorithm in the problems of the rate of empty-loading and minimum distance of working.
出处
《计算机应用研究》
CSCD
北大核心
2017年第2期413-418,共6页
Application Research of Computers
基金
国家自然科学基金资助项目(71471110
71301101)
上海市科委资助项目(14170501500)
关键词
边装边卸
进出口箱簇组合
集卡调度
启发式算法
自适应遗传算法
loading and unloading
import and export container groups
yard truck scheduling
heuristic algorithm
adaptive genetic algorithm
