Computing the Set of Approximate Solutions ...
Document type :
Partie d'ouvrage
Title :
Computing the Set of Approximate Solutions of an MOP with Stochastic Search Algorithms
Author(s) :
Schuetze, Oliver [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Coello Coello, Carlos [Auteur]
Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional [CINVESTAV]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Coello Coello, Carlos [Auteur]
Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional [CINVESTAV]
Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Publication date :
2007
English keyword(s) :
multi-objective optimization
convergence
epsilon-dominance
approximate solutions
stoachastic search algorithms
convergence
epsilon-dominance
approximate solutions
stoachastic search algorithms
HAL domain(s) :
Computer Science [cs]/Operations Research [math.OC]
English abstract : [en]
In this work we develop a framework for the approximation of the entire set of $\epsilon$-efficient solutions of a multi-objective optimization problem with stochastic search algorithms. For this, we propose the set of ...
Show more >In this work we develop a framework for the approximation of the entire set of $\epsilon$-efficient solutions of a multi-objective optimization problem with stochastic search algorithms. For this, we propose the set of interest, investigate its topology and state a convergence result for a generic stochastic search algorithm toward this set of interest. Finally, we present some numerical results indicating the practicability of the novel approach.Show less >
Show more >In this work we develop a framework for the approximation of the entire set of $\epsilon$-efficient solutions of a multi-objective optimization problem with stochastic search algorithms. For this, we propose the set of interest, investigate its topology and state a convergence result for a generic stochastic search algorithm toward this set of interest. Finally, we present some numerical results indicating the practicability of the novel approach.Show less >
Language :
Anglais
Audience :
Non spécifiée
Popular science :
Non
Collections :
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