Bhabani Shankar Prasad Mishra
KIIT University, India.
Title: An Experimental Study of Parallel Multi-objective Genetic Algorithms
Biography
Biography: Bhabani Shankar Prasad Mishra
Abstract
Many of the optimization problems in the real world are multi-objective in nature, and non-dominated Sorting Genetic Algorithm (NSGA II)is commonly used as a problem solving tool.However, 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 NSGA II (i.e., non- Parallel NSGA II) may fail to solve in ï¥-tolerable amount of time.In this context, we can argue that parallel processing techniquescan be a suitable tool of choice to overcome this difficulty. In this paper we study three different modelsi.e., trigger, island,andcone separation to parallelize NSGA-IIto solve multi-objective 0/1 knapsack problem. Further,we emphasize on two factors that can scale the parallelism i.e., convergence and time. The experimental results confirm that cone separation model is showing a clear edge over trigger and island models in terms of processing time and approximation to the true Pareto front.