Deb, Kalyanmoy (2007) Current trends in evolutionary multi-objective optimization International Journal for Simulation and Multidisciplinary Design Optimization, 1 (1). pp. 1-8. ISSN 1779-627X
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Official URL: http://www.ijsmdo.org/index.php?option=com_article...
Related URL: http://dx.doi.org/10.1051/ijsmdo:2007001
Abstract
In a short span of about 14 years, evolutionary multi-objective optimization (EMO) has established itself as a mature field of research and application with an extensive literature, many commercial softwares, numerous freely downloadable codes, a dedicated biannual conference running successfully four times so far since 2001, special sessions and workshops held at all major evolutionary computing conferences, and full-time researchers from universities and industries from all around the globe. In this paper, we make a brief outline of EMO principles, some EMO algorithms, and focus on current research and application potential of EMO. Besides, simply finding a set of Pareto-optimal solutions, EMO research has now diversified in hybridizing its search with multi-criterion decision-making tools to arrive at a single preferred solution, in utilizing EMO principle in solving different kinds of single-objective optimization problems efficiently, and in various interesting application domains which were not possible to be solved adequately due to the lack of a suitable solution technique.
Item Type: | Article |
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Source: | Copyright of this article belongs to EDP Sciences. |
ID Code: | 9461 |
Deposited On: | 02 Nov 2010 12:10 |
Last Modified: | 16 May 2016 19:15 |
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