摘要
以最小化完工时间、最小化碳排放为目标,建立船舶组立混流生产线低碳调度模型,并提出一种多目标混合麻雀搜索算法进行求解。基于离散问题设计一种二维向量编码方式,利用排序值规则实现连续位置与离散调度之间的转换;采用基于混沌映射和反向学习策略的种群初始化来改善初始解的质量;在保留麻雀搜索算法框架的基础上融合粒子群算法和鸡群算法,同时采取多种混合策略来提高算法的寻优能力;通过算例试验测试和某船厂的生产实例仿真验证了模型和多目标算法的有效性。
Aiming at minimizing completion time and carbon emission,a low carbon scheduling model is established and a multi-objective mixed sparrow search algorithm is proposed to solve the problem.Based on the discrete problem,a two-dimensional vector encoding method is designed and the ROV rule is used to realize the conversion between continuous position and discrete scheduling;The population initialization based on chaotic mapping and backward learning strategy is adopted to improve the quality of the initial solution;The particle swarm algorithm and chicken swarm algorithm are integrated on the basis of retaining the SSA algorithm framework,while various hybrid strategies are adopted to improve the algorithm's merit-seeking ability;The effectiveness of the model and the multi-objective algorithm is verified by experimental tests and the simulation of a production example in a shipyard.
作者
苏航
周宏根
李磊
王磊
SU Hang;ZHOU Honggen;LI Lei;WANG Lei(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212100,Jiangsu,China)
出处
《船舶工程》
CSCD
北大核心
2023年第6期1-7,20,共8页
Ship Engineering
基金
国家重点研发计划(2020YFB1712600,2020YFB1712602)
国防基础科研计划项目(JCKY2021414B011)
工信部高技术船舶项目(CJ07N20)
广东省海洋经济发展(海洋六大产业)专项资金项目(粤自然资合[2021]44号)。
关键词
组立装焊线
混合麻雀搜索算法
多目标调度
低碳调度
assembly welding line
hybrid sparrow search algorithm
multi-objective scheduling
low-carbon scheduling
