An analysis of the solution quality of the simple genetic algorithm

Authors:
Haldun Aytug;Anand Paul
Affiliations:
Information Systems and Operations Management Department, Warrington College of Business, University of Florida, Gainesville, FL;Information Systems and Operations Management Department, Warrington College of Business, University of Florida, Gainesville, FL
Venue:
BICA'12 Proceedings of the 5th WSEAS congress on Applied Computing conference, and Proceedings of the 1st international conference on Biologically Inspired Computation
Year:
2012

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Abstract

We introduce a probabilistic worst case bound on the solution quality for the simple genetic algorithm. Given a probability and number of iterations a simple genetic algorithm has performed we show how to bound the distance between the best solution found and the optimal. We introduce several concepts needed for the analysis. The ideas are illustrated on several well-known functions used in the analysis of genetic algorithms.