Title :

What if we increase the number of objectives? Theoretical and empirical implications for many-objective combinatorial optimization

Author(s) :

Allmendinger, Richard [Auteur]
University of Manchester [Manchester]
Jaszkiewicz, Andrzej [Auteur]
Institute of Computing Science [Poznan]
Liefooghe, Arnaud [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Optimisation de grande taille et calcul large échelle [BONUS]
Tammer, Christiane [Auteur]
Martin-Luther-Universität Halle Wittenberg [MLU]

Journal title :

Computers and Operations Research

Pages :

105857

Publisher :

Elsevier

Publication date :

2022

ISSN :

0305-0548

English keyword(s) :

Multi- and many-objective optimization
Problem characteristics
Complexity of procedures and algorithms
Survey
Theoretical and empirical analysis

HAL domain(s) :

Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Computer Science [cs]/Operations Research [math.OC]
Mathématiques [math]/Optimisation et contrôle [math.OC]

English abstract : [en]

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 ...
Show more >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 combinatorial optimization problems (multi-objective NK-landscapes). 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.Show less >

Language :

Anglais

Popular science :

Non

ANR Project :

Optimisation Multiobjectif Big

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL