Robust optimization is a methodology that can be applied to problems that are affected by uncertainty in the problem's parameters. The classical robust counterpart (RC) of the problem requires the solution to be feasible for all uncertain parameter values in a so-called uncertainty set, and...

Burke, Carillo and Vakharia [2009] consider a class of single product sourcing problems with a stochastic demand and multiple uncertain suppliers. Assuming that the demand is independent of the supplier reliabilities and uniformly distributed, they propose to write the expected profit as a...

In this paper we provide a systematic way to construct the robust counterpart of a nonlinear uncertain inequality that is concave in the uncertain parameters. We use convex analysis (support functions, conjugate functions, Fenchel duality) and conic duality in order to convert the robust...

Problems dealing with the design and the operations of gas transmission networks arechallenging. The difficulty mainly arises from the simultaneous modeling of gastransmission laws and of the investment costs. The combination of the two yields a nonlinearnon-convex optimization problem. To...

Burke, Carillo and Vakharia [2009] consider a class of single product sourcing problems with a stochastic demand and multiple uncertain suppliers. Assuming that the demand is independent of the supplier reliabilities and uniformly distributed, they propose to write the expected profit as a...