The maximin fitness function can be used in multi-objective geneticalgorithms to obtain a diverse set of non-dominated designs. The maximinfitness function is derived from the definition of dominance, and its propertiesare explored. The modified maximin fitness function is proposed. Both fitnessfunctions are briefly compared to a state-of-the-art fitness function from theliterature. Results from a real-world multi-objective problem are presented.This problem addresses land-use and transportation planning for high-growthcities and metropolitan regions.
CITATION STYLE
Fonseca, CarlosM., Fleming, PeterJ., Zitzler, E., Thiele, L., Deb, K., & Balling, R. (2012). Lectures on Logic and Computation. (N. Bezhanishvili & V. Goranko, Eds.), Evolutionary Multi-Criterion Optimization (Vol. 7388, pp. 1–15). Springer Berlin Heidelberg. Retrieved from http://dx.doi.org/10.1007/3-540-36970-8_1 http://link.springer.com/10.1007/978-3-642-31485-8
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