Mobile handset selection using evolutionary multi-objective optimization considering the cost and quality parameters

Abstract

Multi-objective optimization is a mathematical framework to deal with conflicting objectives simultaneously. Evolutionary algorithms are extremely useful in implementing multi-objective optimization problems resulting into a new research area named Evolutionary Multi-objective Optimization (EMO). This paper also implements the problem of mobile handset selection considering two objectives which are conflicting, cost and quality of the handset using EMO. The problem is implemented using ‘gamultobj’ solver available in Matlab ‘optimization’ toolbox. The results are shown using Pareto Front at different number of generations.