摘要
为改善船舶分段堆场调度主要依靠经验的现状,建立了带有分段进场时间窗约束,以最小化分段移动度为目标的堆场调度模型.提出采用多链DNA遗传算法对分段的移动顺序、放置位置和运输路径进行优化,并分别采用5种阻挡分段移动策略进行求解.最后,以船厂实际生产数据作为输入,检验遗传算法的有效性和5种移动策略的调度效果.实验表明,多链DNA遗传算法具有较好的收敛性,通过不同输入参数下各种移动策略的对比,可知移动策略2的调度结果最优,能够有效减少分段的非增值运输.
In order to improve the current status of shipbuilding yard scheduling, a scheduling model of shipbuilding yard was established with time window constraints on block inbound and block move degree as the objective to be minimized. A multi-chain DNA genetic algorithm was proposed to optimize the move sequence, placing location and transportation route of the blocks. Besides, five strategies for moving the obstructive blocks were proposed. Using the real production data of a shipbuilding factory as the input, the effectiveness of genetic algorithm and the scheduling results of the five obstructive block moving strategies were verified. Experimental results show that the multi-chain DNA genetic algorithm is easy to converge. A comparison of the results of the five moving strategies obtained with different input parameters proves the superior of the 2nd strategy, which can reduce the non-value-adding transportation of ship blocks effectively.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2016年第9期1390-1398,共9页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金资助项目(71501125)
工业和信息化部项目(工信部联装[2014]507号)
关键词
进场时间窗
分段堆场调度
移动策略
多链DNA遗传算法
inbound time window
shipbuilding yard scheduling
moving strategy
multi-chain DNA genetic algorithm
