We propose a two-stage stochastic programming framework for designing or identifying “resilient”, or “reparable” structures in graphs whose topology may undergo a stochastic transformation. The reparability of a subgraph satisfying a given property is defined in terms of a budget constraint, which allows for a prescribed number of vertices to be added to or removed from the subgraph so as to re...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DECOMPOSITION ALGORITHMS FOR TWO-STAGE STOCHASTIC INTEGER PROGRAMMING By John H. Penuel, Jr. August 2009 Chair: J. Cole Smith Major: Industrial and Systems Engineering Stochastic programming seeks to optimize decision making in uncertain...

We propose a two-stage stochastic programming framework for designing or identifying “resilient”, or “repairable” structures in graphs whose topology may undergo a stochastic transformation. The repairability of a subgraph satisfying a given property is defined in terms of a budget constraint, which allows for a prescribed number of vertices to be added to or removed from the subgraph so as to ...

Opportunities to make sequential decisions and adjust activities as a season progresses and more information becomes available characterise the farm management process. In this paper, we present a discrete stochastic two-stage utility efficient programming model of organic dairy farms, which includes risk aversion in the decision maker’s objective function as well as both embedded risk (stochas...

We consider two-stage stochastic programming problems with integer recourse. The L-shaped method of stochastic linear programming is generalized to these problems by using generalized Benders decomposition. Nonlinear feasibility and optimality cuts are determined via general duality theory and can be generated when the second stage problem is solved by standard techniques. Finite convergence of...

The significant penetration rate of wind turbines in power systems made some challenges in the operation of the systems such as large-scale power fluctuations induced by wind farms. Gas-fired plants with fast starting ability and high ramping can better handle natural uncertainties of wind power compared to other traditional plants. Therefore, the integration of electrical and natural gas syste...

Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, in this study a two-stage stochastic mixed-integer non-linear programing is used to model the o...

In this paper, a stochastic programming approach is applied to the airline network revenue management problem. The airline network with the arc capacitated single hub location problem based on complete–star p-hub network is considered. We try to maximize the profit of the transportation company by choosing the best hub locations and network topology, applying revenue management techniques to al...

This paper presents an optimization model for planning tool purchases for a semiconductor manufacturing facility under uncertain operating conditions. By modeling the uncertain parameters using a scenario tree, we develop a stochastic programming formulation for the problem. In contrast to earlier two-stage approaches for this problem, our model allows for revision of the tool purchase plan as ...

In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic programming problems can be solved with a reasonable accuracy by Monte Carlo sampling techniques while there are indications that complexity of multistage programs grows fast with increase of the number of stages. We ...