A Guide for Fitness Function Design

Abstract

Fitness function design is often both a design and performance bottleneck for evolutionary algorithms. The fitness function for a given problem is directly related to the specifications for that problem. This paper outlines a guide for transforming problem specifications into a fitness function. The target audience for this guide are both non-expert practitioners and those interested in formalizing fitness function design. The goal is to investigate and formalize the fitness function generation process that expert developers go through and in doing so make fitness function design less of a bottleneck. Solution requirements in the problem specifications are identified and classified, then an appropriate fitness function component is generated based on its classifications, and finally the fitness function components combined to yield a fitness function for the problem in question. The competitive performance of a guide generated fitness function is demonstrated by comparing it to that of an expert designed fitness function.

Meeting Name

13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 (2011: Jul. 12-16, Dublin, Ireland)

Department(s)

Computer Science

Sponsor(s)

Missouri University of Science and Technology. Natural Computation Laboratory

Keywords and Phrases

Evolutionary Algorithm; Fitness Function Classification; Fitness Function Design

International Standard Book Number (ISBN)

978-1450306904

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2011 Association for Computing Machinery (ACM), All rights reserved.

Publication Date

01 Jan 2011

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