基于改进NSGA-Ⅱ算法的船舶舾装作业计划优化研究
Optimization of Ship Outfitting Operation Plan Based on Improved NSGA-Ⅱ Algorithm
王森 1范世东 2鲁文 3刘爱华1
作者信息
- 1. 武汉理工大学船海与能源动力工程学院 武汉 430063
- 2. 武汉理工大学交通与物流工程学院 武汉 430063
- 3. 中国船舶集团海舟系统技术有限公司 上海 200011
- 折叠
摘要
针对船舶舾装作业计划编制效率低、计划编制结果不符合作业预期要求等问题,建立多执行模式资源限制条件下的工期、成本和资源多目标优化模型.提出改进的非支配排序遗传算法(NS-GA-Ⅱ),采用随机交叉算子、贪婪变异算子和自适应进化概率提升种群进化效率,同时融合模拟退火算法,增强算法的局部搜索能力,利用改进算法对实例进行仿真计算.结果表明:该方法可对船舶舾装作业计划进行多目标优化控制,实现舾装作业计划智能优化编制.通过算法对比分析,验证了改进NSGA-Ⅱ算法的可行性和有效性.
Abstract
Aiming at the problems of low efficiency in the planning of ship outfitting operation,and the planning results do not meet the expected requirements of operation,a multi-objective optimization model of time limit,cost and resources under the condition of multi-execution mode resource restric-tion was established.An improved non-dominated sorting genetic algorithm(NSGA-Ⅱ)was pro-posed,which used random crossover operator,greedy mutation operator and adaptive evolutionary probability to improve the efficiency of population evolution.Meanwhile,the simulated annealing al-gorithm was combined to enhance the local search ability of the algorithm,and the improved algorithm was used to simulate the example.The results show that this method can carry out multi-objective op-timal control of ship outfitting operation plan and realize intelligent optimal compilation of outfitting operation plan.Through the comparative analysis of the algorithms,the feasibility and effectiveness of the improved NSGA-Ⅱ algorithm are verified.
关键词
船舶舾装/计划编制/多目标优化/NSGA-ⅡKey words
ship outfitting/planning/multi objective optimization/NSGA-Ⅱ引用本文复制引用
基金项目
工信部高技术船舶专项资金(TC19083WB)
出版年
2024
NETL
NSTL
万方数据