[1]汤可宗,詹棠森,李佐勇,等.一种求解置换流水车间调度问题的多策略粒子群优化[J].南京理工大学学报(自然科学版),2019,43(01):48.[doi:10.14177/j.cnki.32-1397n.2019.43.01.007]
 Tang Kezong,Zhan Tangsen,Li Zuoyong,et al.Multi-strategy particle swarm optimization for solvingpermutation flow-shop scheduling problem[J].Journal of Nanjing University of Science and Technology,2019,43(01):48.[doi:10.14177/j.cnki.32-1397n.2019.43.01.007]
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一种求解置换流水车间调度问题的多策略粒子群优化()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
43卷
期数:
2019年01期
页码:
48
栏目:
出版日期:
2019-02-28

文章信息/Info

Title:
Multi-strategy particle swarm optimization for solvingpermutation flow-shop scheduling problem
文章编号:
1005-9830(2019)01-0048-06
作者:
汤可宗1詹棠森1李佐勇2舒 云1
1.景德镇陶瓷大学 信息工程学院,江西 景德镇 333403; 2.工业机器人应用福建省高校工程研究中心,闽江学院,福建 福州 350121
Author(s):
Tang Kezong1Zhan Tangsen1Li Zuoyong2Shu Yun1
1.School of Information Engineering,Jingdezhen Ceramic Institute,Jingdezhen 333403,China; 2.Industrial Robot Application of Fujian University Engineering Research Center,Minjiang University,Fuzhou 350121,China
关键词:
粒子群优化 置换流水车间调度问题 多策略粒子群优化方法 多样性
Keywords:
particle swarm optimization permutation flow-shop scheduling problem multi-strategy particle swarm optimization method diversity
分类号:
TP391.41
DOI:
10.14177/j.cnki.32-1397n.2019.43.01.007
摘要:
为了提高粒子群优化方法解决组合优化问题的效率,该文基于多种组合优化策略,提出一种求解置换流水车间调度问题的多策略粒子群优化方法。该方法基于万有引力值划分的子区间,按信息熵方式度量粒子群体的多样性。同时在蚂蚁路径选择的基础上,综合考虑粒子间距离和惯性质量择优选出全局最优粒子。此外,一种新颖的集合变异方式被用于引导粒子群体跳出局部最优解区域,增强粒子群体的全局搜索能力。测试问题的仿真结果表明,所提出方法能加快最优解的收敛速度和搜索性能,可有效应用于置换流水车间调度问题的求解。
Abstract:
In order to improve the search performance of combinatorial optimization problem for particle swarm optimization,a multi-strategy particle swarm optimization method is proposed for solving permutation flow-shop scheduling problems based on various combinatorial optimization strategies. The proposed method uses information entropy to measure the population diversity of particle group through the sub interval of gravitational value partition. At the same time,the global optimal particle selection is selected by ant routing selection strategy and considering the distance between particles and the mass of inertia. In addition,a novel mutation is designed to guide particle swarm to jump out of the local optimal solution area and enhance the global search ability of particle swarm. The simulation results of test problems show that the multi-strategy particle swarm optimization can effectively accelerate the search performance and convergence speed of the optimal solution,and it can be effectively applied to solve the permutation flow-shop scheduling problem.

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备注/Memo

备注/Memo:
收稿日期:2018-03-12 修回日期:2018-08-13
基金项目:国家自然科学基金(61662037; 71763013); 江西省教育厅科技项目(GJJ170764); 江西省杰出青年人才计划资助(20171bc b23069); 福建省高校青年自然基金重点项目(JZ160467); 工业机器人应用福建省高校工程研究中心开放基金资助(MJUKF-IRA201808)
作者简介:汤可宗(1978-),男,博士,副教授,主要研究方向:智能信息处理,E-mail:tangkezong@126.com。
引文格式:汤可宗,詹棠森,李佐勇,等. 一种求解置换流水车间调度问题的多策略粒子群优化[J]. 南京理工大学学报,2019,43(1):48-53.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2019-02-28