Titre :

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

Auteur(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]

Titre de la revue :

Computers and Operations Research

Pagination :

105857

Éditeur :

Elsevier

Date de publication :

2022

ISSN :

0305-0548

Mot(s)-clé(s) en anglais :

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

Discipline(s) HAL :

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

Résumé en anglais : [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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Optimisation Multiobjectif Big

Collections :

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

Source :

Harvested from HAL