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Abstract: Mu l ip often conflicting objectives arise naturalj in most real worl optimization scenarios. As evol tionaryalAxjO hms possess several characteristics that are desirabl e for this type of probl em, this clOv of search strategies has been used for mul tiobjective optimization for more than a decade. Meanwhil e evol utionary mul tiobjective optimization has become establ ished as a separate subdiscipl ine combining the fiel ds of evol utionary computation and cl assical mul tipl e criteria... (Update)
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BibTeX entry: (Update)
E. Zitzler, M. Laumanns, S. Bleuler, A Tutorial on Evolutionary Multiobjective Optimization, Workshop on Multiple Objective Metaheuristics (MOMH 2002), Springer-Verlag, Berlin, Germany, 2004. http://citeseer.ist.psu.edu/zitzler03tutorial.html More
@misc{ zitzler02tutorial,
author = "E. Zitzler and M. Laumanns and S. Bleuler",
title = "A Tutorial on Evolutionary Multiobjective Optimization",
text = "E. Zitzler, M. Laumanns, S. Bleuler, A Tutorial on Evolutionary Multiobjective
Optimization, Workshop on Multiple Objective Metaheuristics (MOMH 2002),
Springer-Verlag, Berlin, Germany, 2004.",
year = "2002",
url = "citeseer.ist.psu.edu/zitzler03tutorial.html" }
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