A new Pareto frontier covering strategy in FS-MOGA for multi-objective function optimization

This paper presents a new Pareto frontier covering strategy for the functional-specialization multi-objective genetic algorithm (FS-MOGA). FS-MOGA is a real-coded GA for multi-objective function optimization proposed by Hamada et. al. FS-MOGA utilizes the local-Pareto-optima overcoming strategy and...

Full description

Saved in:
Bibliographic Details
Published in:2012 Joint 6th International Conference on Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS) pp. 1888 - 1893
Main Authors: Miyazaki, R., Hamada, N., Nagata, Y., Ono, I.
Format: Conference Proceeding
Language:English
Japanese
Published: IEEE 01.11.2012
ISBN:9781467327428, 1467327425
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents a new Pareto frontier covering strategy for the functional-specialization multi-objective genetic algorithm (FS-MOGA). FS-MOGA is a real-coded GA for multi-objective function optimization proposed by Hamada et. al. FS-MOGA utilizes the local-Pareto-optima overcoming strategy and the Pareto frontier covering strategy adaptively. Hamada et. al. reported that FS-MOGA outperformed conventional methods on multimodal and nonlinear problems. However, the Pareto frontier covering strategy proposed by Hamada et. al. has some problems in terms of the coverage of solution. Especially in case of solving three or more objective problems, the strategy's problems become more critical. In this paper, we propose a new Pareto frontier covering strategy that is excellent in the coverage of solutions and confirm its effectiveness through some experiments.
ISBN:9781467327428
1467327425
DOI:10.1109/SCIS-ISIS.2012.6505313