INTEGRATED GA AND FIREFLY BASED SCHEDULING TECHNIQUE FOR PARALLEL COMPUTING

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Published: Oct 20, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i8.4642
Keywords:
Parallel computing, Scheduling, Genetic algorithm, Firefly algorithm

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Davinderjit Kaur
Guru Nanak Dev University, Amritsar
Er.Amit chabbra

Abstract

This paper has focused on a new Meta heuristic technique i.e. GA+ FIREFLY Hybrid algorithm for parallel job scheduling problem. It has been observed that in existing literature has introduced genetic algorithm which solve parallel job scheduling problem but the genetic algorithm suffers from local optima problem. Moreover it converges slowly so more time it takes to provide the final results. In order to eliminate this problem further improvement has been required to get the sub optimal solution as well as Firefly algorithm works on global optima. It is flexible, robust. Moreover, it uses few parameters as compared to GA and it can be easily hybridized with GA. This research has proposed the hybridisation of GA and Firefly which has done the work on various parameters like make span, flow time, mean waiting time, normalization function etc. The experimental results will also be drawn in order to find the best decomposition among the available one.

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Vol. 8 No. 8 (2017): September-October
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