摘要
内河集装箱运输差异化特征导致船方配载决策时考虑多目标优化,为满足船舶运输经济性和适航性需求,以优化船舶堆栈占用数量、阻塞箱数量、稳性高度、横倾角值及纵倾值为目标,构建内河集装箱船舶配载多目标优化模型。为实现多目标优化问题有效求解,采用灰熵并行分析法改进第三代非支配遗传算法(Non-dominated Sorting Genetic Algorithm-Ⅲ,NSGA-Ⅲ),将灰熵并行关联度作为适应度值引导算法进行精英选择。结果表明:改进后算法在求解性能表现上优于采用一般选择策略的算法,对算例参数设置具有较好鲁棒性,可为船方实际制定内河集装箱船舶配载计划提供一定决策支持。
The diversity of inland container transportation requires multi-objective optimization in ship stowage planning.Aiming to satisfy the requirements of ship transportation economy and seaworthiness,a multi-objective optimization model for stowage of inland container ships is built.The model,based on NSGA-Ⅲ(Non-dominated Sorting Genetic Algorithm-Ⅲ),is developed to comprehensively optimize the number of ship stacks,number of blocking boxes,stability height,roll angle and pitch value.For effectively solving the problem,the grey-entropy parallel analysis method is used to improve the NSGA-Ⅲ algorithm,and the grey entropy parallel correlation degree is used as the guidance algorithm of fitness value for elite selection.The advantage of the algorithm and its robustness are demonstrated.
作者
赵雅洁
李俊
肖笛
温想
ZHAO Yajie;LI Jun;XIAO Di;Wen Xiang(School of Automobile and Traffic Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《中国航海》
CSCD
北大核心
2023年第3期153-162,共10页
Navigation of China
基金
湖北省教育厅科学技术研究计划项目(Q20211110)。
关键词
水路运输
船舶配载
多目标优化
第三代非支配遗传算法
灰熵并行分析
waterway transport
ship stowage planning
multi-objective optimization
NSGA-Ⅲ
grey entropy parallel analysis
