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Title: Multi-objective evolutionary algorithms using the working point and the TOPSIS method
Authors: Méndez, Máximo 
Galván, Blas 
UNESCO Clasification: 1203 Ciencia de los ordenadores
Keywords: Multi-objective optimization
Working point
Decision Making
Evolutionary algorithms
Issue Date: 2007
Journal: Lecture Notes in Computer Science 
Conference: 11th International Conference on Computer Aided Systems Theory 
11th International Conference on Computer Aided Systems Theory, EUROCAST 2007 
Abstract: The use of Multi-Ojective Evolutionary Algorithm (MOEA) methodologies, distinguished for its aptitude to obtain a representative Pareto optimal front, cannot always be the most appropriate. In fact, there exist multi-objective engineering problems that identify one feasible solution in the objective space known as Working Point (WP), not necessarily Pareto optimal. In this case, a Decision Maker (DM) can be more interested in a small number of solutions, for example, those that located in a certain region of the Pareto optimal set (the WP-region) dominate the WP. In this paper, we propose WP-TOPSISGA, an algorithm which merges the WP, MOEA techniques and the Multiple Criteria Decision Making (MCDM) method TOPSIS. With TOPSIS, a DM only needs input the preferences or weights wi, with our method, however, the weights are evaluated by interpolation in every iteration of the algorithm. The idea is to guide the search of solutions towards the WP-region, giving an order to the found solutions in terms of Similarity to the Ideal Solution.
ISBN: 978-3-540-75866-2
ISSN: 0302-9743
DOI: 10.1007/978-3-540-75867-9_100
Source: Moreno Díaz R., Pichler F., Quesada Arencibia A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelb
Appears in Collections:Actas de congresos
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