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A Hybrid Parallel Multi-Objective Genetic Algorithm for 0/1 Knapsack Problem

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DOI: 10.4236/jsea.2011.45035    4,017 Downloads   7,537 Views   Citations


In this paper a hybrid parallel multi-objective genetic algorithm is proposed for solving 0/1 knapsack problem. Multi-objective problems with non-convex and discrete Pareto front can take enormous computation time to converge to the true Pareto front. Hence, the classical multi-objective genetic algorithms (MOGAs) (i.e., non- Parallel MOGAs) may fail to solve such intractable problem in a reasonable amount of time. The proposed hybrid model will combine the best attribute of island and Jakobovic master slave models. We conduct an extensive experimental study in a multi-core system by varying the different size of processors and the result is compared with basic parallel model i.e., master-slave model which is used to parallelize NSGA-II. The experimental results confirm that the hybrid model is showing a clear edge over master-slave model in terms of processing time and approximation to the true Pareto front.

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The authors declare no conflicts of interest.

Cite this paper

S. Jagtap, S. Pani and G. Shinde, "A Hybrid Parallel Multi-Objective Genetic Algorithm for 0/1 Knapsack Problem," Journal of Software Engineering and Applications, Vol. 4 No. 5, 2011, pp. 316-319. doi: 10.4236/jsea.2011.45035.


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