A Multi-objective Optimization Method Based on Nelder–Mead Simplex Search Method

Abstract

In this paper, a method based on Nelder and Mead’s simplex search method is developed for solving multi-objective optimization problems. Unlike other multi-objective optimization algorithms based on classical methods, this method does not require any a priori knowledge about the problem. Moreover, it does not need any pre-defined weights or additional constraints as it works without scalarizing the multi-objective problem. The algorithm works with a population of points and is capable of generating a multitude of Pareto optimal solutions. Equipped with the constraint handling strategy adopted in this work, the method is found to be competitive with respect to the existing algorithms.