A review of scenario generation methods
by Sovan Mitra, Nico Di Domenica
International Journal of Computing Science and Mathematics (IJCSM), Vol. 3, No. 3, 2010

Abstract: Stochastic programming models provide a powerful paradigm for decision making under uncertainty. In these models the uncertainties are captured by scenario generation and so are crucial to the quality of solutions obtained. Presently there do not exist many literature reviews on scenario generation; this paper surveys them. We introduce the main concepts behind scenario generation, which are not just concerned with discretising methods. We review the main scenario generation classes and analyse the advantages and disadvantages. We also review new and less commonly known scenario generation methods, such as 'hybrid' methods.

Online publication date: Mon, 13-Dec-2010

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