Current trends in evolutionary multi-objective optimization

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

PDF - Publisher Version

Official URL:

Related URL:


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
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

Repository Staff Only: item control page