TITLE:
A Hybrid Parallel Multi-Objective Genetic Algorithm for 0/1 Knapsack Problem
AUTHORS:
Sudhir B. Jagtap, Subhendu Kumar Pani, Ganeshchandra Shinde
KEYWORDS:
Multi-Objective Genetic Algorithm, Parallel Processing Techniques, NSGA-II, 0/1 Knapsack Problem, Trigger Model, Cone Separation Model, Island Model
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.4 No.5,
May
26,
2011
ABSTRACT: 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.