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MP
2006
87views more  MP 2006»
13 years 5 months ago
Convexity and decomposition of mean-risk stochastic programs
Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
Shabbir Ahmed
MP
2006
110views more  MP 2006»
13 years 5 months ago
Robust game theory
We present a distribution-free model of incomplete-information games, both with and without private information, in which the players use a robust optimization approach to contend ...
Michele Aghassi, Dimitris Bertsimas
MP
2006
103views more  MP 2006»
13 years 5 months ago
Assessing solution quality in stochastic programs
Determining if a solution is optimal or near optimal is fundamental in optimization theory, algorithms, and computation. For instance, Karush-Kuhn-Tucker conditions provide necessa...
Güzin Bayraksan, David P. Morton
MP
2006
107views more  MP 2006»
13 years 5 months ago
Convergence theory for nonconvex stochastic programming with an application to mixed logit
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Fabian Bastin, Cinzia Cirillo, Philippe L. Toint
MP
2006
87views more  MP 2006»
13 years 5 months ago
A Robust Optimization Approach to Dynamic Pricing and Inventory Control with no Backorders
In this paper, we present a robust optimization formulation for dealing with demand uncertainty in a dynamic pricing and inventory control problem for a make-to-stock manufacturing...
Elodie Adida, Georgia Perakis