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Constructing dynamic optimization test problems using the multi-objective optimization concept.

Jin, Y and Sendhoff, B (2004) Constructing dynamic optimization test problems using the multi-objective optimization concept. In: EvoWorkshops 2004, 2004-04-05 - 2004-04-07, Coimbra, Portugal.

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Official URL: http://dx.doi.org/10.1007/978-3-540-24653-4_53

Abstract

Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typical test functions for comparing the performance of various dynamic optimization algorithms still lack. This paper suggests a method for constructing dynamic optimization test problems using multi-objective optimization (MOO) concepts. By aggregating different objectives of an MOO problem and changing the weights dynamically, we are able to construct dynamic single objective and multi-objective test problems systematically. The proposed method is computationally efficient, easily tunable and functionally powerful. This is mainly due to the fact that the proposed method associates dynamic optimization with multi-objective optimization and thus the rich MOO test problems can easily be adapted to dynamic optimization test functions.

Item Type:Conference or Workshop Item (Paper)
Additional Information:G.R. Raidl et al. (Eds.): EvoWorkshops 2004, LNCS 3005, pp. 525–536, 2004. Copyright Springer-Verlag Berlin Heidelberg 2004 The original publication is available at http://www.springerlink.com
Divisions:Faculty of Engineering and Physical Sciences > Computing Science
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ID Code:7621
Deposited By:Symplectic Elements
Deposited On:09 Mar 2012 09:48
Last Modified:24 Jan 2013 09:15

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