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Abstract: Evolutionary algorithms (EAs) are often wellsuited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a single run. However, the few comparative studies of different methods presented up to now remain mostly qualitative and are often restricted to a few approaches. In this paper, four multiobjective EAs are... (Update)
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BibTeX entry: (Update)
Zitzler, E. and L. Thiele (1999). Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach. IEEE Transactions on Evolutionary Computation. To appear. http://citeseer.ist.psu.edu/zitzler99multiobjective.html More
@article{ zitzler99multiobjective,
author = "Eckart Zitzler and Lothar Thiele",
title = "Multiobjective {E}volutionary {A}lgorithms: {A} {C}omparative {C}ase {S}tudy and the {S}trength {P}areto {A}pproach",
journal = "IEEE Transactions on Evolutionary Computation",
volume = "3",
number = "4",
pages = "257--271",
year = "1999",
url = "citeseer.ist.psu.edu/zitzler99multiobjective.html" }
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