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Scheduling multiple yard cranes in two adjacent container blocks with position-dependent processing times

机译:根据位置的处理时间在两个相邻的集装箱区中调度多台起重机

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摘要

This paper studies the management of three yard cranes in two adjacent container blocks in line, where cranes can move from one block to the other. Comparing with existing literature, the new multi-yard-crane scheduling problem incorporates different constraints together: (i) three yard cranes are deployed simultaneously in two adjacent blocks, (ii) non-crossing and inter-crane interference constraints of yard cranes are considered, (iii) the processing time of each container depends on its real-time location, i.e., position-dependent processing times. For the problem, a 0-1 mixed integer programming (MIP) model is constructed to minimize the total flow time to reduce the total container storage time in container yards, which helps to save container yard resources and increase production efficiency. The proposed model can be solved optimally by CPLEX for small-size instances. As the concerned problem is NP-hard, a fast heuristic and an improved genetic algorithm are devised to produce near-optimal solutions for large-size instances. Numerical experiments validate the developed MIP model and demonstrate the efficiency of the proposed algorithms.
机译:本文研究了串联的两个相邻集装箱区中的三台起重机的管理,其中起重机可以从一个区移动到另一个区。与现有文献相比,新的多院子起重机调度问题将不同的约束结合在一起:(i)在两个相邻的区块中同时部署三台院子起重机,(ii)考虑了院子起重机的非交叉和起重机间干扰约束,(iii)每个容器的处理时间取决于其实时位置,即与位置有关的处理时间。针对该问题,构建了0-1混合整数规划(MIP)模型,以最大程度地减少总流动时间,从而减少集装箱堆场中的集装箱总存放时间,这有助于节省集装箱堆场资源并提高生产效率。对于小型实例,CPLEX可以最佳地解决所提出的模型。由于所关注的问题是NP难题,因此设计了一种快速启发式算法和一种改进的遗传算法来为大型实例提供接近最优的解决方案。数值实验验证了所开发的MIP模型并证明了所提出算法的效率。

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