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作 者:许波桅 接德培 李军军[2] 杨勇生 XU Bowei;JIE Depei;LI Junjun;YANG Yongsheng(Institute of Logistics Science and Engineering,Shanghai Maritime University,Shanghai 201306,China;College of Merchant Marine,Shanghai Maritime University,Shanghai 201306,China)
机构地区:[1]上海海事大学物流科学与工程研究院,上海201306 [2]上海海事大学商船学院,上海201306
出 处:《计算机集成制造系统》2022年第12期4057-4068,共12页Computer Integrated Manufacturing Systems
基 金:国家自然科学基金资助项目(52102466);上海市自然科学基金资助项目(21ZR1426900)。
摘 要:为了提高U型自动化码头的装卸效率,促进绿色港口的发展。针对U型自动化码头“双小车岸桥+自动导引车(AGV)+双悬臂轨道吊+外集卡”的装卸工艺,考虑外集卡到达的不确定性,运用混合流水车间调度相关理论,提出一种绿色等待策略,建立了以所有任务的完工时间最小和装卸设备碳排放量最少的多目标绿色集成调度模型,设计了一种改进的混合遗传布谷鸟算法对模型进行求解。通过小、中、大规模的集装箱作业任务实验,将混合遗传布谷鸟算法与遗传算法、自适应遗传算法、灰狼优化算法进行对比,验证了提出的模型与算法的有效性。结果表明,当任务规模较小时,不等待策略的结果较好,并且随着任务量的增多,两者的差值逐渐减小;当任务规模较大时,等待策略结果较好。To improve the operating efficiency of U-shaped automated container terminal and to promote the development of green port,aiming at the loading and unloading process of"dual trolley quay crane+Automated Guided Vehicle(AGV)+dual cantilever rail crane+external truck",considering the uncertainty of external truck arrival,a green waiting strategy was proposed by using the related theory of hybrid flow shop scheduling.With the goal of minimizing the completion time of all tasks and minimizing carbon emission of operating equipment,a multi-objective green integrated scheduling model was constructed and an improved hybrid genetic cuckoo algorithm was designed to solve the model.Through small,medium and large-scale container operation task experiments,the proposed algorithm was compared with genetic algorithm,adaptive genetic algorithm and grey wolf optimizer algorithm to verify its effectiveness.The results showed that the result of no wait strategy was better when the task size was small,and with the increase of task size,the difference between them decreased gradually.When the task scale was large,the result of waiting strategy was better.
关 键 词:U型自动化码头 绿色集成调度 混合遗传布谷鸟算法 不确定性 能耗
分 类 号:U691.3[交通运输工程—港口、海岸及近海工程]
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