Int. J. Simul. Multidisci. Des. Optim.
Volume 1, Number 1, October 2007
|Page(s)||1 - 8|
|Published online||12 December 2007|
Current trends in evolutionary multi-objective optimization
Department of Mechanical Engineering, Indian Institute of Technology Kanpur, PIN 208016, India
Corresponding author: email@example.com
Accepted: 25 September 2007
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.
© ASMDO, EDP Sciences, 2007
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