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 ...
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...
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...
Decomposition algorithms such as Lagrangian relaxation and Dantzig-Wolfe decomposition are well-known methods that can be used to generate bounds for mixed-integer linear programmi...
We study two different lot-sizing problems with time windows that have been proposed recently. For the case of production time windows, in which each client specific order must be ...