摘要
针对传统优化方法空间利用率不足这一问题对杂货船的装载问题进行研究,在分析杂货船装载特点的基础上,建立以空间利用率为目标的装货数学模型。在此基础上,同时分析启发式算法和遗传算法获得改进遗传算法,基于改进遗传算法设计一种新的杂货船装载优化算法,并通过实验验证了该算法的有效性和实用性。以文献经典中的一组测试数据为例,对同类型算法进行对比分析。结果表明,基于改进遗传算法的平均空间利用率为98.56%,与其他算法相比具有明显的优势。
Aiming at the problem of insufficient space utilization of traditional optimization methods,the loading problem of general cargo ships is studied.Based on the analysis of the loading characteristics of general cargo ships,a mathematical model of loading with space utilization as the goal is established.On this basis,combining heuristic algorithm and genetic algorithm,a new general cargo ship loading optimization algorithm was designed,and the effectiveness and practicability of the algorithm were verified through experiments.Taking a set of test data in the literature classic as an example,a comparative analysis of the same type of algorithm is performed.The results show that the average space utilization rate based on the improved genetic algorithm is 98.56%,which has obvious advantages compared with other algorithms.
作者
尚晓峰
SHANG Xiao-feng(City Institute,Dalian University of Technology,Management School,Dalian 116600,China)
出处
《舰船科学技术》
北大核心
2020年第14期1-3,共3页
Ship Science and Technology
基金
辽宁省自然科学基金指导计划项目(20180550438)
关键词
遗传算法
杂货船
装载优化
优化方法
genetic algorithm
general cargo ship
loading optimization
optimization method
