A complex and typical scheduling problem in waterway transportation: co-scheduling of cascaded locks with multiple chambers (CCLM) is studied. Based on in-depth analysis of the problem properties, the CCLM is handled by separating it into three interconnected subproblems, each with a simpler structure and higher flexibility to be handled. The outer layer and inner layer concerns the sum of lockage number and ship placement, respectively. The interlayer as a connection bridge between the other two refers to lockage direction combination and timetable optimization which is a high-dimensional mixed integer optimization problem. To solve the CCLM problem, a hybrid approach based on iteration which mainly combines quantum inspired binary gravitational search algorithm and modified moth-flame optimization algorithm is proposed. In addition, two different scheduling rules which are usually concerned in practice, the area utilization maximization and first-come-first-served (FCFS) rule, are also tested in the CCLM problem. Experiments are conducted on instances that are extracted from real world data. The scheduling and comparison results verify that the CCLM problem can be well handled by the proposed method.

中文翻译：

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多室级联锁协同调度的混合智能方法


研究了水路运输中一个复杂且典型的调度问题：多室级联船闸协同调度（CCLM）。基于对问题属性的深入分析，CCLM的处理方式是将其分解为三个相互关联的子问题，每个子问题的结构更简单，处理灵活性更高。外层和内层分别涉及船闸数量和船舶位置的总和。夹层作为连接两者的桥梁，是指船闸方向组合和时刻表优化，是一个高维混合整数优化问题。为了解决CCLM问题，提出了一种基于迭代的混合方法，主要结合了量子启发二元引力搜索算法和改进的飞蛾火焰优化算法。此外，在CCLM问题中还测试了实践中经常关注的两种不同的调度规则，即区域利用率最大化和先来先服务（FCFS）规则。实验是在从现实世界数据中提取的实例上进行的。调度和比较结果验证了该方法可以很好地处理CCLM问题。