A tabu-genetic hybrid search algorithm for job-shop scheduling problem

Yan Ge, Aimin Wang, Zijin Zhao, Jieran Ye

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)

Abstract

To deal with the job-shop scheduling problem (JSP), a tabu-genetic hybrid search algorithm is proposed. The algorithm generates several initial solutions distributed in the whole solution space for tabu search by genetic algorithm, which avoids the over-dependence on the initial solution of tabu search algorithm. With the mechanism mentioned above, the algorithm proposed has both global search performance of genetic algorithm and local search performance of labu search algorithm. Finally, a program was developed with the achral data of FT (10x 10).To verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.

Original languageEnglish
Article number04007
JournalE3S Web of Conferences
Volume95
DOIs
Publication statusPublished - 13 May 2019
Event3rd International Conference on Power, Energy and Mechanical Engineering, ICPEME 2019 - Prague, Czech Republic
Duration: 16 Feb 201919 Feb 2019

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