Metaheuristic Design Pattern: Surrogate Fitness Functions

Citation

Brownlee A, Woodward J & Swan J (2016) Metaheuristic Design Pattern: Surrogate Fitness Functions. In: 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, 11.07.2015-15.07.2015. New York: ACM, pp. 1261-1264. https://doi.org/10.1145/2739482.2768499

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.

People

Dr Sandy Brownlee

Senior Lecturer in Computing Science, Computing Science and Mathematics - Division