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A Hybrid Intelligent Approach for Co-Scheduling of Cascaded Locks With Multiple Chambers

机译:混合智能多箱级联锁联合调度方法。

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摘要

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.
机译:水路运输中一个复杂而典型的调度问题:研究了多舱级联锁的联合调度(CCLM)。基于对问题属性的深入分析,通过将CCLM分为三个相互联系的子问题来处理CCLM,每个子问题具有更简单的结构和更高的处理灵活性。外层和内层分别涉及锁定数量和船舶布置的总和。作为其他两者之间的连接桥梁的中间层是指锁定方向组合和时间表优化,这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,该方法主要结合了量子启发式二进制引力搜索算法和改进的蛾-火焰优化算法。另外,在CCLM问题中还测试了实践中通常会涉及的两个不同的调度规则:区域利用率最大化和先到先得(FCFS)规则。对从现实世界数据中提取的实例进行实验。调度和比较结果验证了该方法能够很好地处理CCLM问题。

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