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Exploiting Genetic algorithm towards CPU Scheduling


Monika Mangla , lokmanya tilak college of engineering; Rakhi Akhare, LTCE, Koparkhairane; Smita Ambarkar, LTCE, Koparkhairane


CPU Scheduling, NP Hard, Genetic Algorithm, Crossover, Mutation, Selection


Scheduling has become a problem of keen interest as a result of its widespread application in all areas. Effective scheduling approaches results in maximum utilization of resources. As scheduling in problem of interest to various researchers, various novel techniques are being proposed by various researchers to use the resources in an efficient and effective manner. Various heuristic have also been combined with different techniques to solve scheduling problems. Here, in this paper, we discuss how genetic algorithm can be used to solve CPU scheduling problems in an innovative manner. The same technique can be used for scheduling any resource. To attempt the problem of CPU scheduling, we use efficient encoding, and design appropriate crossover and mutation operators. Each individual is an encoded version of a proposed solution. The proposed approach consists of the individuals evaluation, their selection, which will contribute to the next generation using recombination of the parents by means of crossover, mutation and other operators.

Other Details

Paper ID: IJSRDV3I60470
Published in: Volume : 3, Issue : 6
Publication Date: 01/09/2015
Page(s): 1134-1137

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