关键词: 多目标优化问题, 基于分解的多目标进化算法, 花朵授粉算法, 非支配解, 基于网格的方法

Abstract: During the past decades, a variety of multi-objective evolutionary algorithms (MOEAs) have been widely used to solve all kinds of multi-objective optimization problems (MOPs). One of the representative MOEAs is the multi-objective evolution algorithm based on decomposition, called MOEA/D. The flower pollination algorithm (FPA) is a meta-heuristic optimization algorithm. However, to our best knowledge, so far there are few papers studying on FPA based on decomposition in the multi-objective optimization field. In this paper, under the framework of MOEA/D, we extend the initial FPA to decomposed-based multi-objective optimization field and further present a multi-objective FPA based on decomposition, called MOFPA/D. In addition, in order to keep the diversity of nondominated solutions in the external archive, we address a novel strategy, named grid-based segmentation of objective space to select some Pareto optimal solutions for output. The simulation results indicate that MOFPA/D is highly competitive with or superior to the initial MOEA/D in terms of solution convergence and diversity.

Key words: multi-objective optimization problems, decomposed-based multi-objective evolutionary algorithm, flower pollination algorithm, nondominated solutions, grid-based approach