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Abstract: We present a new heuristic method to approximate the set of Pareto-optimal solutions in multi-criteria optimization problems. We use genetic algorithms with an adaptive selection mechanism. The direction of the selection pressure is adapted to the actual state of the population and forces it to explore a broad range of so far undominated solutions. The adaptation is done by a fuzzy rule based control of the selection procedure and the fitness function. As an application we present a timetable... (Update)
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...that will guide the search to the particular Pareto region that is of interest to the decision maker. Finally, Voget and Kolonko [100] proposed the use of a fuzzy controller that regulates the selection pressure automatically by using a set of predefined goals that...
...utility function) that will guide the search to the particular Pareto region that is of interest to the decision maker. Finally, Voget and Kolonko [1998] proposed the use of a fuzzy controller that regulates the selection pressure automatically by using a set of predefined goals...
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BibTeX entry: (Update)
S. Voget and M. Kolonko. Multidimensional Optimization with a Fuzzy Genetic Algorithm. Journal of Heuristics, 1998. (In Press). http://citeseer.ist.psu.edu/758696.html More
@article{ voget98multidimensional,
author = "Stefan Voget and Michael Kolonko",
title = "Multidimensional {O}ptimization with a {F}uzzy {G}enetic {A}lgorithm",
journal = "Journal of Heuristics",
volume = "4",
number = "3",
pages = "221--244",
year = "1998",
url = "citeseer.ist.psu.edu/758696.html" }
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