DocumentCode :
555662
Title :
Hybrid VNS and memetic algorithm for solving the job shop scheduling problem
Author :
Wang, Bing-gang ; Zhang, Guo-hui
Author_Institution :
Res. Inst. of Bus. Adm., Henan Univ. of Urban Constr., Pingdingshan, China
Volume :
Part 2
fYear :
2011
fDate :
3-5 Sept. 2011
Firstpage :
924
Lastpage :
927
Abstract :
The job shop scheduling problem (JSP) is focused by many researchers which is well known as one of the most complex optimization problems due to its very large search space and many constraint between jobs and machines. It is quite difficult to achieve optimal or near-optimal solutions with single traditional optimization approach. Memetic algorithm (MA) is a hybrid algorithm that combines the local search strategy and global search strategy. In this paper, an novel hybrid algorithm combined variable neighborhood search (VNS) algorithm with memetic algorithm is proposed to solve the JSP. The neighborhood functions is generated by exchanging and inserting the key operations which belong to the critical path. The minimizing makespan is considered as optimization objective. Lastly, benchmark problems is computed, and the results demonstrate the proposed hybrid algorithm is effective and efficient for solving the JSP.
Keywords :
job shop scheduling; minimisation; search problems; JSP; benchmark problems; complex optimization problem; critical path; global search strategy; hybrid VNS; hybrid algorithm; job shop scheduling problem; local search strategy; makespan minimization; memetic algorithm; neighborhood functions; variable neighborhood search algorithm; Algorithm design and analysis; Biological cells; Genetic algorithms; Job shop scheduling; Memetics; Optimization; Search problems; critical path; job shop scheduling; memetic algorithm; variable neighborhood search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IE&EM), 2011 IEEE 18Th International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-61284-446-6
Type :
conf
DOI :
10.1109/ICIEEM.2011.6035308
Filename :
6035308
Link To Document :
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