Running time analysis of a multi-objective evolutionary algorithm on a simple discrete optimization problem
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2002-01
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Report
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Abstract
For the first time, a running time analysis of a multi-objective evolutionary algorithm for a discrete optimization problem is given. To this end, a simple pseudo-Boolean problem (Lotz: leading ones - trailing zeroes) is defined and a population-based optimization algorithm (FEMO). We show, that the algorithm performs a black box optimization in Θ(n2 log n) function evaluations where n is the number of binary decision variables.
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123
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ETH Zurich, Computer Engineering and Networks Laboratory
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02640 - Inst. f. Technische Informatik und Komm. / Computer Eng. and Networks Lab.