- author = "Martin Holena and David Linke and Lukas Bajer",
- title = "Case study: constraint handling in evolutionary optimization of catalytic materials",
- booktitle = "GECCO 2011 Evolutionary computation techniques for constraint handling",
- year = "2011",
- editor = "Carlos Artemio Coello Coello and Dara Curran and Thomas Jansen",
- isbn13 = "978-1-4503-0690-4",
- keywords = "genetic algorithms, genetic programming",
- pages = "333--340",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
DOI = "
doi:10.1145/2001858.2002015",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "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.",
-
notes = "Also known as \cite{2002015} Distributed on CD-ROM at
GECCO-2011.
ACM Order Number 910112.",
