PAMUC: A new method to handle with constraints and multiobjectivity in evolutionary algorithms. Multiobjective optimization using evolutionary algorithms (EA) has become a wide area of research during these last years. However, only a few papers deal with the handling of preferences. To take them into account, a method based on multicriteria decision aid, PROMETHEE II, has been implemented. Furthermore, as the handling of the constraints is very critical in EA, an original approach preferences applied to multiobjectivity and constraints (PAMUC) has been proposed, which considers the satisfaction of the constraints as another objective.
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References in zbMATH (referenced in 8 articles , 1 standard article )
Showing results 1 to 8 of 8.
- Richardson, James N.; Adriaenssens, Sigrid; Bouillard, Philippe; Coelho, Rajan Filomeno: Multiobjective topology optimization of truss structures with kinematic stability repair (2012)
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- Parreiras, R.O.; Vasconcelos, J.A.: A multiplicative version of Promethee II applied to multiobjective optimization problems (2007)
- Filomeno Coelho, R.; Bouillard, Ph.: A multicriteria evolutionary algorithm for mechanical design optimization with expert rules (2005)
- Lagaros, Nikos D.; Plevris, Vagelis; Papadrakakis, Manolis: Multi-objective design optimization using cascade evolutionary computations (2005)
- Filomeno Coelho, R.; Bouillard, Ph.; Bersini, H.: PAMUC: A new method to handle with constraints and multiobjectivity in evolutionary algorithms (2004)
- Greiner, David; Emperador, José María; Winter, Gabriel: Single and multiobjective frame optimization by evolutionary algorithms and the auto-adaptive rebirth operator (2004)
- Filomeno Coelho, R.; Bersini, H.; Bouillard, Ph.: Parametrical mechanical design with constraints and preferences: Application to a purge valve. (2003)