FUZZY FLOW SHOP SCHEDULING USING GREY WOLF OPTIMIZATION ALGORITHM

Journal Title: Indian Journal of Scientific Research - Year 2017, Vol 7, Issue 2

Abstract

Flow shop scheduling is one of the most important optimization problem for which a number of heuristic and metaheuristic techniques have been successfully applied. In this paper, the problem of two machine flow shop scheduling taking into consideration makespan and idle time of both machines has been considered. The numbers of existing approaches are not found to be purely applicable to real time situations due to uncertainties involved. In order to handle such situations, the processing time and setup times of jobs is taken under fuzzy environment. Nature-Inspired Grey Wolf Optimization algorithm has been used to resolve this problem. The results thus obtained are compared to existing heuristic approach as well as other metaheuristic approaches such as multi-objective Genetic Algorithm, Particle Swarm Optimization and NSGA-II algorithm. It is observed that Grey Wolf based approach performs better than other approaches and existing heuristic approach for the problem under consideration.

Authors and Affiliations

KAWAL JEET

Keywords

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  • EP ID EP370085
  • DOI -
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How To Cite

KAWAL JEET (2017). FUZZY FLOW SHOP SCHEDULING USING GREY WOLF OPTIMIZATION ALGORITHM. Indian Journal of Scientific Research, 7(2), 167-171. https://europub.co.uk/articles/-A-370085