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17-11-2015 | Methodologies and Application

Nadir point estimation for many-objective optimization problems based on emphasized critical regions

Authors: Handing Wang, Shan He, Xin Yao

Published in: Soft Computing | Issue 9/2017

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Abstract

Nadir points play an important role in many-objective optimization problems, which describe the ranges of their Pareto fronts. Using nadir points as references, decision makers may obtain their preference information for many-objective optimization problems. As the number of objectives increases, nadir point estimation becomes a more difficult task. In this paper, we propose a novel nadir point estimation method based on emphasized critical regions for many-objective optimization problems. It maintains the non-dominated solutions near extreme points and critical regions after an individual number assignment to different critical regions. Furthermore, it eliminates similar individuals by a novel self-adaptive \(\varepsilon \)-clearing strategy. Our approach has been shown to perform better on many-objective optimization problems (between 10 objectives and 35 objectives) than two other state-of-the-art nadir point estimation approaches.

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Title: Nadir point estimation for many-objective optimization problems based on emphasized critical regions
Authors: Handing Wang
Shan He
Xin Yao
Publication date: 17-11-2015
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 9/2017
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-015-1940-x

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