The objective of this paper is to bring systematic methods for scenario tree generation to the attention of the Process Systems Engineering community. In this paper, we focus on a general, data-driven optimization-based method for generating scenario trees, which does not require strict assumptions on the probability distributions of the uncertain parameters. This method is based on the Moment ...

In this paper, we develop a multi-objective stochastic programming approach for supply chain design under uncertainty. Demands, supplies, processing, transportation, shortage and capacity expansion costs are all considered as the uncertain parameters. To develop a robust model, two additional objective functions are added into the traditional comprehensive supply chain design problem. So, our m...

At present, cloud providers can offer cloud consumers three provisioning plans for computing resources, namely on-demand instance, reserved instance and spot instance. On-demand instance is stable, but very expensive; reserved instance is also guaranteed, and advance reservations are required, however customers’ future demands are often uncertain; price of spot instance could be the cheapest, b...

We begin this paper by identifying a class of stochastic mixed-integer programs that have column-oriented formulations suitable for solution by a branch-and-price algorithm (B&P). We then survey a number of examples, and use a stochastic facility-location problem (SFLP) for a detailed demonstration of the relevant modeling and solution techniques. Computational results with a scenario represent...

Increased firm formalization helps emerging firms develop stable routines and processes to increase their chances of survival. However, uncertain and dynamic task environments of emerging firms require more flexible organizational structures. Such duality of structural prescriptions stems from competing demands of task and institutional environments. We propose that manufacturing flexibility co...

We consider a variant of the single item lot sizing problem where the product, when stored, suffers from a proportional loss, and in which the product demand is affected by uncertainty. This setting is particularly relevant in the energy sector, where the demands must be satisfied in a timely manner and storage losses are, often, unavoidable. We propose a two-stage robust optimization approach ...

In this note we discuss the system optimum dynamic traffic assignment (SO-DTA) problem in the presence of time-dependent uncertainty on the demands and link capacities. We start from the deterministic linear programming formulation of the SO-DTA problem introduced by Ziliaskopoulos in [14], and then consider a robust version of the decision problem where the total travel time must be minimized ...

We consider a sequential two-party bargaining game with uncertain information transmission. When the first mover states her demand she does only know the probability with which the second mover will be informed about it. The informed second mover can either accept or reject the offer and payoffs are determined as in the ultimatum game. Otherwise the uninformed second mover states his own demand...

This talk deals with the problem of capacity expansion of a network under independent uncertain demands defined by interval sets. In this context, decisions about capacity expansion must be made before the demands are revealed. Standard robust models require the definition of an uncertainty domain and look for the minimum cost solution able to satisfy any demand within this domain. We propose, ...

Intra-domain traffic engineering is essential for the operation of an Internet Service Provider (ISP). Demandoblivious routing [5] promises excellent performance guarantee with changing and uncertain traffic demands. However, it is non-trivial to implement it. We investigate an efficient and deployable implementation of oblivious routing. We study its performance by both numerical experiments a...