Performance consequences of introducing an internal penalty function to a genetic algorithm for scheduling

Authors:
Michael Doherty;Chih-Cheng Hung
Affiliations:
Southern Polytechnic State University, Marietta, GA;Anyang Normal University, State University, Marietta, GA
Venue:
Proceedings of the 2013 Research in Adaptive and Convergent Systems
Year:
2013

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Abstract

In this paper, we describe the effects of adding an internal penalty function of variable severity in a genetic algorithm used to design a schedule as opposed to using no penalty function. The use of the penalty function was found to decrease the average number of generations needed to find an optimal solution when used in moderation and to cause premature convergence when used in excess.