|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||Metaheuristic Design Pattern: Surrogate Fitness Functions|
|Citation:||Brownlee A, Woodward J & Swan J (2016) Metaheuristic Design Pattern: Surrogate Fitness Functions, Silva S (ed.) GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, GECCO 2015: Annual Conference on Genetic and Evolutionary Computation, Madrid, Spain, 11.7.2015 - 15.7.2015, New York: ACM, pp. 1261-1264.|
|Conference Name:||GECCO 2015: Annual Conference on Genetic and Evolutionary Computation|
|Conference Location:||Madrid, Spain|
|Abstract:||Certain problems have characteristics that present difficulties for metaheuristics: their objective function may be either prohibitively expensive, or they may only give a partial ordering over the solutions, lacking a suitable gradient to guide the search. In such cases, it may be more efficient to use a surrogate fitness function to replace or supplement the objective function. This paper provides a broad perspective on surrogate fitness functions, described in the form of a metaheuristic design pattern.|
|Status:||Book Chapter: author post-print (pre-copy editing)|
|Rights:||Publisher policy allows this work to be made available in this repository. Published in GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation by ACM. The original publication is available at: http://dl.acm.org/citation.cfm?id=2768499|
|Affiliation:||Computing Science - CSM Dept|
Computing Science and Mathematics
Computing Science - CSM Dept
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