The integration of renewable generation poses operational and economic challenges for the electricity grid. For the core problem of power balance, the legacy paradigm of tailoring supply to follow random demand may be inappropriate under deep penetration of uncertain and intermittent renewable generation. In this situation, there is an emerging consensus that the alternative approach of control...

1 We extend the existing toll pricing studies with fixed demand to stochastic demand. A new and 2 practical second-best pricing problem with uncertain demand is proposed and formulated as a 3 stochastic mathematical program with equilibrium constraints. In view of the problem structure, 4 we develop a tailored global optimization algorithm. This algorithm incorporates a sample 5 average approxi...

Traditional stochastic inventory models assume full knowledge of the demand distribution. However, in practice, it is often difficult to completely characterize the demand distribution, especially with little or outdated historical data. In these uncertain environments, good inventory management has to be robust, i.e., perform well under most demand scenarios. In this paper, we study the newsve...

This paper presents a novel approach to compute optimal machine, shop oor and shell space expansion times under uncertain customer demand. It considers multiple machine types and allows for positive lead times for each type. Demand is assumed to be nondecreasing in a \weak" sense. A polynomial time algorithm (FIFEX) is developed and shown to be eeective and eecient with an example from the Semi...

Despite the existence of several weather studies in the tourism literature, there remain some gaps in knowledge. Uncertainty about weather conditions persists despite the impressive improvements in modern forecasting techniques. This study is a first attempt to investigate how weather uncertainty affects tourism demand. The findings indicate that the impact of weather on tourism demand is likel...

A recent focal point in research on the vehicle routing problem (VRP) is the issue of robustness in which customer demand is uncertain. In this paper, we conduct a theoretical analysis of the demand distributions whose induced workloads are as undesirable as possible. We study two common variations of VRP in a continuous approximation setting: the first is the VRP with time windows, and the sec...

This paper investigates demand forecast and order placement policy of a seasonal product for the retailers in an active business season. In a two-phase demand model, the market demand is uncertain, and decision-making for order placement is addressed for the second phase after observing the demand at the first phase during the active season. The model uses a Poisson process for customer demand ...

As the number of natural disasters and their impacts increase across the globe, the need for effective preparedness against such events becomes more vital. In this paper, we construct a supply chain network optimization model for a disaster relief organization in charge of obtaining, storing, transporting, and distributing relief goods to certain disasterprone regions. Our system-optimization a...

Markov-modulated processes have been used in stochastic inventory models with setup costs for modeling demand under the innuence of uncertain environmental factors, such as uctuat-ing economic and marketing conditions. The analyses of these models have been carried out in the literature only under the assumption that unsatissed demand is fully backlogged. We study a Markovian demand model in th...

Determining the optimum number of suppliers and the optimum quantities to order from each of them is a critical problem for any supply chain. This paper has mathematically arrived at conditions to identify the appropriate sourcing strategy in a multi-period scenario for a stochastic supply and a stochastic demand environment. It has also obtained the total order quantity, optimum number of supp...