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2015 | OriginalPaper | Chapter

3. An Extension of the MOON2/MOON2R Approach to Many-Objective Optimization Problems

Author : Yoshiaki Shimizu

Published in: Optimization Methods, Theory and Applications

Publisher: Springer Berlin Heidelberg

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Abstract

A multi-objective optimization (MUOP) method that supports agile and flexible decision making to be able to handle complex and diverse decision environments has been in high demand. This study proposes a general idea for solving many-objective optimization (MAOP) problems by using the MOON2 or MOON2R method. These MUOP methods rely on prior articulation in trade-off analysis among conflicting objectives. Despite requiring only simple and relative responses, the decision maker’s trade-off analysis becomes rather difficult in the case of MAOP problems, in which the number of objective functions to be considered is larger than in MUOP. To overcome this difficulty, we present a stepwise procedure that is extensively used in the analytic hierarchy process. After that, the effectiveness of the proposed method is verified by applying it to an actual problem. Finally, a general discussion is presented to outline the direction of future work in this area.

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previous chapter Rearrangement Optimization Problems Related to a Class of Elliptic Boundary Value Problems
next chapter Existence of Solutions for Variational-Like Hemivariational Inequalities Involving Lower Semicontinuous Maps
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Metadata
Title
An Extension of the MOON2/MOON2R Approach to Many-Objective Optimization Problems
Author
Yoshiaki Shimizu
Copyright Year
2015
Publisher
Springer Berlin Heidelberg
Book
Optimization Methods, Theory and Applications

Print ISBN: 978-3-662-47043-5

Electronic ISBN: 978-3-662-47044-2

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-662-47044-2_3

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