[1]裴小兵,张春花.应用改进区块遗传算法求解置换流水车间调度问题[J].智能系统学报,2019,14(3):541-550.[doi:10.11992/tis.201801041]
 PEI Xiaobing,ZHANG Chunhua.An improved puzzle-based genetic algorithm for solving permutation flow-shop scheduling problems[J].CAAI Transactions on Intelligent Systems,2019,14(3):541-550.[doi:10.11992/tis.201801041]
点击复制

应用改进区块遗传算法求解置换流水车间调度问题

参考文献/References:
[1] 周明, 孙树栋. 遗传算法原理及应用[M]. 北京:国防工业出版社, 1999:6.
[2] 夏小云, 周育人. 蚁群优化算法的理论研究进展[J]. 智能系统学报, 2016, 11(1):27-36 XIA Xiaoyun, ZHOU Yuren. Advances in theoretical research of ant colony optimization[J]. CAAI transactions on intelligent systems, 2016, 11(1):27-36
[3] 李金忠, 夏洁武, 曾小荟, 等. 多目标模拟退火算法及其应用研究进展[J]. 计算机工程与科学, 2013, 35(8):77-88 LI Jinzhong, XIA Jiewu, ZENG Xiaohui, et al. Survey of multi-objective simulated annealing algorithm and its applications[J]. Computer engineering and science, 2013, 35(8):77-88
[4] TAYEB F B S, BESSEDIK M, BENBOUZID M, et al. Research on permutation flow-shop scheduling problem based on improved genetic immune algorithm with vaccinated offspring[J]. Procedia computer science, 2017, 112:427-436.
[5] CHEN Rongchang, CHEN J, CHEN T S, et al. Synergy of genetic algorithm with extensive neighborhood search for the permutation flowshop scheduling problem[J]. Mathematical problems in engineering, 2017, 2017:3630869.
[6] BESSEDIK M, TAYEB F B S, CHEURFI H, et al. An immunity-based hybrid genetic algorithms for permutation flowshop scheduling problems[J]. International journal of advanced manufacturing technology, 2016, 85(9/10/11/12):2459-2469.
[7] GANGULY S, MUKHERJEE S, BASU D, et al. A novel strategy adaptive genetic algorithm with greedy local search for the permutation flowshop scheduling problem[M]//Swarm, Evolutionary, and Memetic Computing. Berlin, Heidelberg:Springer, 2012:687-696.
[8] 齐学梅, 王宏涛, 陈付龙, 等. 求解多目标PFSP的改进遗传算法[J]. 计算机工程与应用, 2015, 51(11):242-247 QI Xuemei, WANG Hongtao, CHEN Fulong, et al. Improved genetic algorithm for multi-objective of PFSP[J]. Computer engineering and applications, 2015, 51(11):242-247
[9] 崔琪, 吴秀丽, 余建军. 变邻域改进遗传算法求解混合流水车间调度问题[J]. 计算机集成制造系统, 2017, 23(9):1917-1927 CUI Qi, WU Xiuli, YU Jianjun. Improved genetic algorithm variable neighborhood search for solving hybrid flow shop scheduling problem[J]. Computer integrated manufacturing systems, 2017, 23(9):1917-1927
[10] CHANG P C, HUANG W H, WU J L, et al. A block mining and re-combination enhanced genetic algorithm for the permutation flowshop scheduling problem[J]. International journal of production economics, 2013, 141(1):45-55.
[11] JIN Jian. A hybrid discrete biogeography-based optimization for the permutation flow shop scheduling problem[J]. International journal of production research, 2016, 54(16):4805-4814.
[12] DORIGO M, GAMBARDELLA L M. Ant colony system:a cooperative learning approach to the traveling salesman problem[J]. IEEE transactions on evolutionary computation, 1997, 1(1):53-66.
[13] 陈慧芬. 基于链结学习的子群体进化算法求解多目标调度问题[D]. 天津:天津理工大学, 2017. CHEN Huifen. Sub-population evolutionary algorithm based on linkage learning for multi-objective scheduling problem[D]. Tianjin:Tianjin University of Technology, 2017.
[14] 裴小兵, 陈慧芬, 张百栈, 等. 改善式BVEDA求解多目标调度问题[J]. 山东大学学报(工学版), 2017, 47(4):25-30 PEI Xiaobing, CHEN Huifen, ZHANG Baizhan, et al. Improved bi-variables estimation of distribution algorithms for multi-objective permutation flow shop scheduling problem[J]. Journal of Shandong University (engineering science), 2017, 47(4):25-30
[15] 裴小兵, 赵衡. 基于二元分布估计算法的置换流水车间调度方法[J]. 中国机械工程, 2017, 28(22):2752-2759 PEI Xiaobing, ZHAO Heng. Permutation flow shop scheduling problem based on hybrid binary distribution estimation algorithm[J]. China mechanical engineering, 2017, 28(22):2752-2759
[16] 张敏, 汪洋, 方侃. 基于改进区块进化算法求解置换流水车间问题[J]. 计算机集成制造系统, 2018, 24(5):1207-1216 ZHANG Min, WANG Yang, FANG Kan. Improved block-based evolutionary algorithm for solving permutation flowshop scheduling problem[J]. Computer integrated manufacturing systems, 2018, 24(5):1207-1216
[17] CHANG P C, CHEN Menghui. A block based estimation of distribution algorithm using bivariate model for scheduling problems[J]. Soft computing, 2014, 18(6):1177-1188.
[18] MILLER B L, GOLDBERG D E. Genetic algorithms, tournament selection, and the effects of noise[J]. Complex systems, 1995, 9(3):193-212.
[19] CHANG P C, CHEN S H, FAN C Y, et al. Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems[J]. Annals of operations research, 2010, 180(1):197-211.
[20] HSU C Y, CHANG P C, CHEN M H. A linkage mining in block-based evolutionary algorithm for permutation flowshop scheduling problem[J]. Computers & industrial engineering, 2015, 83:159-171.
相似文献/References:
[1]李枝勇,马良,张惠珍.多目标0-1规划问题的蝙蝠算法[J].智能系统学报,2014,9(6):672.[doi:10.3969/j.issn.1673-4785.201310038]
 LI Zhiyong,MA Liang,ZHANG Huizhen.Bat algorithm for the multi-objective 0-1 programming problem[J].CAAI Transactions on Intelligent Systems,2014,9():672.[doi:10.3969/j.issn.1673-4785.201310038]
[2]夏小云,周育人.蚁群优化算法的理论研究进展[J].智能系统学报,2016,11(1):27.[doi:10.11992/tis.201510002]
 XIA Xiaoyun,ZHOU Yuren.Advances in theoretical research of ant colony optimization[J].CAAI Transactions on Intelligent Systems,2016,11():27.[doi:10.11992/tis.201510002]
[3]胡志强,李文静,乔俊飞.带扰动的变频正弦混沌神经网络研究[J].智能系统学报,2018,13(4):493.[doi:10.11992/tis.201703003]
 HU Zhiqiang,LI Wenjing,QIAO Junfei.Frequency-conversion sinusoidal chaotic neural network with disturbance feature[J].CAAI Transactions on Intelligent Systems,2018,13():493.[doi:10.11992/tis.201703003]
[4]裴小兵,孙志卫.改进区块遗传算法解决分布式车间调度问题[J].智能系统学报,2021,16(2):303.[doi:10.11992/tis.201906035]
 PEI Xiaobing,SUN Zhiwei.Solving distributed-shop scheduling problems based on modified genetic algorithm[J].CAAI Transactions on Intelligent Systems,2021,16():303.[doi:10.11992/tis.201906035]

备注/Memo

收稿日期:2018-01-23。
基金项目:国家创新方法工作专项项目(2017IM060200);天津市哲学社会科学规划项目(TJYY17-013).
作者简介:裴小兵,男,1965生,教授,博士,主要研究方向为生产调度、精益生产。发表学术论文14篇;张春花,女,1992生,硕士研究生,主要研究方向为生产调度、智能算法。
通讯作者:张春花.E-mail:Zhang_chunhua1203@126.com

更新日期/Last Update: 1900-01-01
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134