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Case study: constraint handling in evolutionary optimization of catalytic materials
- 1.0362974 - ÚI 2012 RIV US eng C - Conference Paper (international conference)
Holeňa, Martin - Linke, D. - Bajer, Lukáš
Case study: constraint handling in evolutionary optimization of catalytic materials.
GECCO '11 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. New York: ACM, 2011 - (Krasnogor, N.), s. 333-339. ISBN 978-1-4503-0690-4.
[GECCO 2011. Genetic and Evolutionary Computation Conference /13./. Dublin (IE), 12.07.2011-16.07.2011]
R&D Projects: GA ČR GA201/08/0802; GA ČR GAP202/11/1368
Institutional research plan: CEZ:AV0Z10300504
Keywords : evolutionary optimization * mixed optimization * equality constraints * inequality constraints * cardinality constraints
Subject RIV: IN - Informatics, Computer Science
The paper presents a case study in an industrially important application domain the optimization of catalytic materials. Though evolutionary algorithms are the by far most frequent approach to optimization tasks in that domain, they are challenged by mixing continuous and discrete variables, and especially by a large number of constraints. The paper describes the various kinds of encountered constraints, and explains constraint handling in GENACAT, one of evolutionary optimization systems developed specifically for catalyst optimization. In particular, it is shown that the interplay between cardinality constraints and linear equality and inequality constraints allows GENACAT to efficienlty determine the set of feasible solutions, and to split the original optimization task into a sequence of discrete and continuous optimization. Finally, the genetic operations employed in the discrete optimization are sketched, among which crossover is based on an assumption about the importance of the choice of sets of continuous variables in the cardinality constraints.
Permanent Link: http://hdl.handle.net/11104/0199135
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