Differential Evolution for Solving multiobjective Optimization Problems

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. The objective of this paper is to introduce a novel Pareto–frontier Differential Evolution (PDE) algorithm to solve VOPs. The solutions provided by the proposed algorithm for two standard test problems , outperform the Strength Pareto Evolutionary Algorithm, one of the state-of-the-art evolutionary algorithm for solving VOPs.