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Case study: constraint handling in evolutionary optimization of catalytic materials
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SYSNO ASEP 0362974 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Case study: constraint handling in evolutionary optimization of catalytic materials Tvůrce(i) Holeňa, Martin (UIVT-O) SAI, RID
Linke, D. (DE)
Bajer, Lukáš (UIVT-O) SAI, RID, ORCIDZdroj.dok. GECCO '11 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. - New York : ACM, 2011 / Krasnogor N. - ISBN 978-1-4503-0690-4 Rozsah stran s. 333-339 Poč.str. 7 s. Akce GECCO 2011. Genetic and Evolutionary Computation Conference /13./ Datum konání 12.07.2011-16.07.2011 Místo konání Dublin Země IE - Irsko Typ akce WRD Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova evolutionary optimization ; mixed optimization ; equality constraints ; inequality constraints ; cardinality constraints Vědní obor RIV IN - Informatika CEP GA201/08/0802 GA ČR - Grantová agentura ČR GAP202/11/1368 GA ČR - Grantová agentura ČR CEZ AV0Z10300504 - UIVT-O (2005-2011) EID SCOPUS 80051952288 DOI 10.1145/2001858.2002015 Anotace 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. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2012
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