Worst-Case-Expectation Approach to Optimization Under Uncertainty

Alexander Shapiro; Wajdi Tekaya; Murilo Pereira Soares; Joari Paulo da Costa

doi:10.1287/opre.2013.1229

Worst-Case-Expectation Approach to Optimization Under Uncertainty

Alexander Shapiro¹; Wajdi Tekaya²; Murilo Pereira Soares³; Joari Paulo da Costa³

¹ School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 · ² Cambridge Systems Associates, Cambridge CB5 8AF, United Kingdom · ³ Operador Nacional do Sistema Elétrico, Rio de Janeiro, RJ 20211-160, Brazil

Operations Research 2013

In this paper we discuss multistage programming with the data process subject to uncertainty. We consider a situation where the data process can be naturally separated into two components: one can be modeled as a random process, with a specified probability distribution, and the other one can be treated from a robust (worst-case) point of view. We formulate this in a time consistent way and derive the corresponding dynamic programming equations. To solve the obtained multistage problem, we develop a variant of the stochastic dual dynamic programming method. We give a general description of the algorithm and present computational studies related to planning of the Brazilian interconnected power system.

DOI: 10.1287/opre.2013.1229
Volume: 61 (6)
Pages: 1435-1449
Language: en
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