A Novel Variable Neighborhood Genetic Algorithm for Multi-objective Flexible Job-Shop Scheduling Problems

被引:6
作者
Zhang, Guohui [1 ]
Gao, Liang [2 ]
Shi, Yang [2 ]
机构
[1] Zhengzhou Inst Aeronaut Ind Management, Zhengzhou, Peoples R China
[2] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Peoples R China
来源
MATERIALS AND PRODUCT TECHNOLOGIES | 2010年 / 118-120卷
关键词
Flexible job shop scheduling; Multi objective; Genetic algorithm; Variable neighborhood search;
D O I
10.4028/www.scientific.net/AMR.118-120.369
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Flexible job shop scheduling problem (FJSP) is an important extension of the classical jobshop scheduling problem, where the same operation could be processed on more than one machine. It is quite difficult to achieve optimal or near-optimal solutions with single traditional optimization approach because the multi objective FJSP has the high computational complexity. An novel hybrid algorithm combined variable neighborhood search algorithm with genetic algorithm is proposed to solve the multi objective FJSP in this paper. An external memory is adopted to save and update the non-dominated solutions during the optimization process. To evaluate the performance of the proposed hybrid algorithm, benchmark problems are solved. Computational results show that the proposed algorithm is efficient and effective approach for the multi objective FJSP.
引用
收藏
页码:369 / +
页数:2
相关论文
共 8 条
[1]  
[Anonymous], 2003, HDB METAHEURISTICS
[2]   JOB-SHOP SCHEDULING WITH MULTIPURPOSE MACHINES [J].
BRUCKER, P ;
SCHLIE, R .
COMPUTING, 1990, 45 (04) :369-375
[3]   A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems [J].
Gao, Jie ;
Sun, Linyan ;
Gen, Mitsuo .
COMPUTERS & OPERATIONS RESEARCH, 2008, 35 (09) :2892-2907
[4]   Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic [J].
Kacem, I ;
Hammadi, S ;
Borne, P .
MATHEMATICS AND COMPUTERS IN SIMULATION, 2002, 60 (3-5) :245-276
[5]   A genetic algorithm for the Flexible Job-shop Scheduling Problem [J].
Pezzella, F. ;
Morganti, G. ;
Ciaschetti, G. .
COMPUTERS & OPERATIONS RESEARCH, 2008, 35 (10) :3202-3212
[6]   An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems [J].
Xia, WJ ;
Wu, ZM .
COMPUTERS & INDUSTRIAL ENGINEERING, 2005, 48 (02) :409-425
[7]  
Zhang GH, 2008, LECT NOTES ARTIF INT, V5315, P503, DOI 10.1007/978-3-540-88518-4_54
[8]   An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem [J].
Zhang, Guohui ;
Shao, Xinyu ;
Li, Peigen ;
Gao, Liang .
COMPUTERS & INDUSTRIAL ENGINEERING, 2009, 56 (04) :1309-1318