An Exploration and Exploitation Search Control Scheme for Permutation Flow Shop Problem

被引:0
作者
Chen, Ruey-Maw [1 ]
Wang, Ching-Te [1 ]
Hsu, Chao-Chin [1 ]
机构
[1] Natl Chin Yi Univ Technol, Taichung, Taiwan
来源
2012 7TH INTERNATIONAL CONFERENCE ON COMPUTING AND CONVERGENCE TECHNOLOGY (ICCCT2012) | 2012年
关键词
Permutation flow shop problem (PFSP); simulated annealing (SA); exchange search; insertion search; metaheuristics; HEURISTIC ALGORITHM; M-MACHINE; N-JOB; OPTIMIZATION;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The permutation flow shop problem (PFSP) has been studied by many researches and applied to plenty of applications. The PFSP has been confirmed to be an NP-complete permutation sequencing scheduling problem. Hence, many search schemes for finding near optima of PFSP were proposed. Insertion and exchange are two well used search schemes in finding solutions. Intrinsically, insertion scheme results in large range search (exploration), while exchange scheme corresponding to small range search (exploitation). To enhance the search efficiency by controlling exploration and exploitation abilities, an asymmetric sigmoid decline control in search pace is proposed. Restated, solution search based on designed control strategy starting from exploration towards exploitation is proposed. Meanwhile, a modified SA is included for avoiding trapping on local optimal solution, which the fitness deviation based acceptance criterion is suggested for avoiding acute acceptance probability turbulence. The experimental results demonstrate that the proposed scheme is effective and efficient when comparing with other state-of-the-art methods.
引用
收藏
页码:1298 / 1303
页数:6
相关论文
共 19 条
  • [1] [Anonymous], 1998, Evolutionary Computation Proceedings, DOI DOI 10.1109/ICEC.1998.699146
  • [2] CAMPBELL HG, 1970, MANAGE SCI B-APPL, V16, pB630
  • [3] Chen RM, 2009, 2008 IEEE CONFERENCE ON SOFT COMPUTING IN INDUSTRIAL APPLICATIONS SMCIA/08, P101
  • [4] Ant colony optimization -: Artificial ants as a computational intelligence technique
    Dorigo, Marco
    Birattari, Mauro
    Stuetzle, Thomas
    [J]. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2006, 1 (04) : 28 - 39
  • [5] Glover F., 1998, Tabu Search, DOI DOI 10.1007/978-1-4615-6089-0_1
  • [6] Holland J. H., 1987, Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms, P82
  • [7] Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
  • [8] OPTIMIZATION BY SIMULATED ANNEALING
    KIRKPATRICK, S
    GELATT, CD
    VECCHI, MP
    [J]. SCIENCE, 1983, 220 (4598) : 671 - 680
  • [9] Lei KY, 2006, ISSCAA 2006: 1ST INTERNATIONAL SYMPOSIUM ON SYSTEMS AND CONTROL IN AEROSPACE AND ASTRONAUTICS, VOLS 1AND 2, P977
  • [10] Malik RezaFirsandaya., 2007, International Journal of Computer Science and Security, V1, P35