(Enter summary)
Abstract: After adequately demonstrating the
ability to solve different two-objective optimization
problems, multi-objective evolutionary algorithms
(MOEAs) must now show their efficacy in handling
problems having more than two objectives. In this
paper, we suggest three different approaches for systematically
designing test problems for this purpose.
The simplicity of construction, scalability to any number
of decision variables and objectives, knowledge
of exact shape and location of the resulting... (Update)
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BibTeX entry: (Update)
Kalyanmoy Deb, Lothar Thiele, Marco Laumanns, and Eckart Zitzler. Scalable MultiObjective Optimization Test Problems. In Congress on Evolutionary Computation (CEC'2002), volume 1, pages 825--830, Piscataway, New Jersey, May 2002. IEEE Service Center. http://citeseer.ist.psu.edu/deb02scalable.html More
@misc{ deb02scalable,
author = "K. Deb and L. Thiele and M. Laumanns and E. Zitzler",
title = "Scalable MultiObjective Optimization Test Problems",
text = "Kalyanmoy Deb, Lothar Thiele, Marco Laumanns, and Eckart Zitzler. Scalable
MultiObjective Optimization Test Problems. In Congress on Evolutionary Computation
(CEC'2002), volume 1, pages 825--830, Piscataway, New Jersey, May 2002.
IEEE Service Center.",
year = "2002",
url = "citeseer.ist.psu.edu/deb02scalable.html" }
Citations not processed or no citations identified.
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