Multi-objective optimization using metaheuristics: non-standard algorithms

Talbi, El-Ghazali; Basseur, Matthieu; Nebro, Antonio Jesús; Alba, Enrique

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1111/j.1475-3995.2011.00808.x

Titre :

Multi-objective optimization using metaheuristics: non-standard algorithms

Auteur(s) :

Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Basseur, Matthieu [Auteur]
Laboratoire d'Etudes et de Recherche en Informatique d'Angers [LERIA]
Nebro, Antonio Jesús [Auteur]
Computer Science Department of University of Malaga
Alba, Enrique [Auteur]
Departamento Lenguajes y Ciencias de la Computación [LCC]

Titre de la revue :

International Transactions in Operational Research

Pagination :

283-306

Éditeur :

Wiley

Date de publication :

2012

ISSN :

0969-6016

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]

Résumé en anglais : [en]

In recent years, the application of metaheuristic techniques to solve multi‐objective optimization problems has become an active research area. Solving this kind of problems involves obtaining a set of Pareto‐optimal ...
Lire la suite >In recent years, the application of metaheuristic techniques to solve multi‐objective optimization problems has become an active research area. Solving this kind of problems involves obtaining a set of Pareto‐optimal solutions in such a way that the corresponding Pareto front fulfils the requirements of convergence to the true Pareto front and uniform diversity. Most of the studies on metaheuristics for multi‐objective optimization are focused on Evolutionary Algorithms, and some of the state‐of‐the‐art techniques belong this class of algorithms. Our goal in this paper is to study open research lines related to metaheuristics but focusing on less explored areas to provide new perspectives to those researchers interested in multi‐objective optimization. In particular, we focus on non‐evolutionary metaheuristics, hybrid multi‐objective metaheuristics, parallel multi‐objective optimization and multi‐objective optimization under uncertainty. We analyze these issues and discuss open research lines.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :