A Multi-objective Flower Pollination Algorithm Based on Decomposition

doi:10.3969/j.issn.1006-2475.2019.07.001

Abstract

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

CLC Number:

TP391

CHEN Min-rong, HUANG Guang-jing. A Multi-objective Flower Pollination Algorithm Based on Decomposition[J]. Computer and Modernization, 2019, 0(07): 1-.

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