The treasurer of a bank is responsible for the cash management of several banking activities. In this work we focus on two of them: cash management in automatic teller machines (ATMs), and in the compensation of credit card transactions. In both cases a decision must be taken according to a future customers demand, which is uncertain. From historical data we can obtain a discrete probability di...

Wind power generation is variable and uncertain. In the power systems with high penetration of wind power, determination of equivalent operating reserve is the main concern of systems operator. In this paper, a model is proposed to determine operating reserves in simultaneous market clearing of energy and reserve by stochastic programming based on scenarios generated via Monte Carlo simulation ...

We use distributionally robust stochastic programs (DRSP) to model a general class of newsvendor problems where the underlying demand distribution is unknown, and so the goal is to find an order quantity that minimizes the worst-case expected cost among an ambiguity set of distributions. The ambiguity set consists of those distributions that are not far—in the sense of the so-called variation d...

In this paper, we present a new idea for robust project scheduling combined with a cost-oriented uncertainty investigation. The result of the new approach is a makespan minimal robust proactive schedule, which is immune against the uncertainties in the activity durations and which can be evaluated from a cost-oriented point of view on the set of the uncertain-but-bounded duration and cost param...

We investigate dynamic policies for allocating scarce inventory to stochastic demand for multiple fare classes, in a network environment so as to maximize total expected revenues. Typical applications include sequential reservations for an airline network, hotel, or car rental service. We propose and analyze a new algorithm based on approximate dynamic programming, both theoretically and comput...

We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time. The attractive features of the proposed approach are: (a) It incorporates a wide variety of phenomena, including demands that are not identically distributed over time and capacity on the echelons and links; (b) it uses very ...

Although stochastic programming is probably the most effective frameworks for handling decision problems that involve uncertain variables, it is always a costly task to formulate the stochastic model that accurately embodies our knowledge of these variables. In practice, this might require one to collect a large amount of observations, to consult with experts of the specialized field of practic...

We present a stochastic model for capacity-expansion planning of electricity distribution networks subject to uncertain demand (CEP). We formulate CEP as a multistage stochastic mixed-integer program with a scenario-tree representation of uncertainty. At each node of the scenario-tree, the model determines capacity-expansions, operating con guration, and power ows. A “super-arc” representation ...

A multi-product fish production planning produces simultaneously multi fish products from several classes of raw resources. The goal in production planning is to meet customer demand over a fixed time horizon divided into planning periods by optimizing the trade-off between economic objectives such as production cost and customer satisfaction level. The major decisions are production and invent...