What if we Increase the Number of Objectives? Theoretical and Empirical
Implications for Many-objective Optimization
- URL: http://arxiv.org/abs/2106.03275v1
- Date: Sun, 6 Jun 2021 23:25:35 GMT
- Title: What if we Increase the Number of Objectives? Theoretical and Empirical
Implications for Many-objective Optimization
- Authors: Richard Allmendinger, Andrzej Jaszkiewicz, Arnaud Liefooghe,
Christiane Tammer
- Abstract summary: This paper investigates the influence of the number of objectives on problem characteristics and the practical behavior of commonly used procedures and algorithms for coping with many objectives.
We make use of our theoretical and empirical findings to derive practical recommendations to support algorithm design.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The difficulty of solving a multi-objective optimization problem is impacted
by the number of objectives to be optimized. The presence of many objectives
typically introduces a number of challenges that affect the choice/design of
optimization algorithms. This paper investigates the drivers of these
challenges from two angles: (i) the influence of the number of objectives on
problem characteristics and (ii) the practical behavior of commonly used
procedures and algorithms for coping with many objectives. In addition to
reviewing various drivers, the paper makes theoretical contributions by
quantifying some drivers and/or verifying these drivers empirically by carrying
out experiments on multi-objective NK landscapes and other typical benchmarks.
We then make use of our theoretical and empirical findings to derive practical
recommendations to support algorithm design. Finally, we discuss remaining
theoretical gaps and opportunities for future research in the area of multi-
and many-objective optimization.
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