摘要
针对最小化最大完工时间的柔性作业车间调度问题(Flexible job shop scheduling problem,FJSP),提出了一种新型元启发式算法,鲸鱼群算法(Whale swarm optimization algorithm,WSA),该算法以"较优且最近"的鲸鱼引导和利用超声波强度来控制鲸鱼个体移动范围的迭代方式,在求解各类标准函数时显示出了其在全局搜索能力和维持种群多样性方面的优越性。采用两段式编码方法将FJSP描述为机器选择和工序排序两个子问题;引入转换机制实现FJSP的离散调度解与连续的鲸鱼个体位置向量之间的相互转换,然后利用WSA完成种群的迭代更新和寻优。最后,通过实验数据验证了WSA在求解FJSP方面的有效性。
A new meta-heuristic algorithm,whale swarm algorithm(WSA)is proposed for solving the flexible job shop scheduling problem(FJSP)with the objective to minimize the makespan.In the WSA,whale individual position vector can be updated by using the guidance of its better and most recent whale,the range of whale individual movements can be controlled by the ultrasonic intensity,because of this iteration method,it shows superiority in global searching ability and maintaining population diversity when solving various standard functions.Firstly,a two-segment string is used to describe the FJSP as two sub-problems,machine assignment and operation sequence.Secondly,the conversion method between the whale individual position vector and the scheduling solution is applied,and then the population can be updated and searched for optimization via WSA.Finally,the experimental data show that the present WSA is effective for solving the FJSP.
作者
栾飞
吴书强
李富康
杨嘉
蔡宗琰
Luan Fei;Wu Shuqiang;Li Fukang;Yang Jia;Cai Zongyan(School of Construction Machinery,Chang'an University,Xi'an 710064,China;College of Mechanical and Electrical Engineering,Shaanxi University of Science&Technology,Xi'an 710021,China)
出处
《机械科学与技术》
CSCD
北大核心
2020年第2期241-246,共6页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(11072192)
陕西省软科学研究计划资助项目(2018KRM090)
西安市科技创新引导项目(201805023YD1CG7(1))资助.
关键词
柔性作业车间调度问题
鲸鱼群算法
个体位置向量
调度解
flexible job shop scheduling problem
whale swarm algorithm
individual position vector
scheduling solution
作者简介
栾飞(1983-),讲师,博士研究生,研究方向为生产调度、智能算法,luanfei@sust.edu.cn
