Browsing Volume 2000 by Title
Now showing items 120 of 27

20000704BuchA finite branch and bound algorithm for twostage stochastic integer programs This paper addresses a general class of twostage stochastic programs with integer recourse and discrete distributions. We exploit the structure of the value function of the second stage integer problem to develop a novel ...

20010406BuchA heuristic for generating scenario trees for multistage decision problems In stochastic programming models we always face the problem of how to represent the random variables. This is particularly difficult with multidimensional distributions. We present an algorithm that produces a discrete ...

20000829BuchA note on the connectedness of chance constraints We prove a result on connectedness of (functional) chance constraints $ P(h(x) \ge g(\xi) \ge p$, where the decision variable $x$ belongs to a Banach space and $h$ is assumed to be strictly quasiconcave. The derived ...

20000812BuchA twostage planning model for power scheduling in a hydrothermal system under uncertainty A twostage stochastic programming model for the short or midterm costoptimal electric power production planning is developed. We consider the power generation in a hydrothermal generation system under uncertainty in ...

20001107BuchAdaptive optimal stochastic trajectory planning and control (AOSTPC) for robots In optimal control of robots, the standard procedure is to determine first offline an optimal openloop control, using some nominal or estimated values of the model parameters, and to correct then the resulting deviation ...

20000626BuchConditioning of stochastic programs In this paper we consider stochastic programming problems where the objective function is given as an expected value function. With an optimal solution of such a (convex) problem we associate a condition number which ...

20000407BuchConfidence level solutions for stochastic programming We propose an alternative approach to stochastic programming based on MonteCarlo sampling and stochastic gradient optimization. The procedure is by essence probabilistic and the computed solution is a random variable. The ...

20000613BuchDetermining risk neutral probabilities and optimal portfolio policies in a dynamic investment model with downside risk control in the presence of trading frictions This paper develops an approximate method for solving multiperiod utility maximization investment models with downside risk control characterized by the minimum attainable wealth among all possible scenarios. The stochastic ...

20000216BuchFinite capacity production planning with random demand and limited information Production planning has a fundamental role in any manufacturing operation. The problem is to decide what type of, and how much, product should be produced in future time periods. The decisions should be based on many ...

20000613BuchMeanvariance versus expected utility in dynamic investment analysis This paper derives the meanvariance efficient frontier and optimal portfolio policies for a dynamic investment model. In the absence of arbitrage opportunities, the optimal expected portfolio value can be identified through ...

20000524BuchOptimizing electricity distribution using twostage integer recourse models We consider two planning problems faced by an electricity distributor. Electricity can be obtained both from power plants and small generators such as hospitals and greenhouses, whereas the future demand for electricity ...

20000706BuchOutput analysis for approximated stochastic programs Because of incomplete information and also for the sake of numerical tractability one mostly solves an approximated stochastic program instead of the underlying ''true'' decision problem. However, without an additional ...

20000120BuchPower management in a hydrothermal system under uncertainty by Lagrangian relaxation We present a dynamic multistage stochastic programming model for the costoptimal generation of electric power in a hydrothermal system under uncertainty in load, inflow to reservoirs and prices for fuel and delivery ...

20001005BuchProbabilistic programs with discrete distributions and precedence constrained knapsack polyhedra We consider stochastic programming problems with probabilistic constraints involving random variables with discrete distributions. They can be reformulated as large scale mixed integer programming problems with knapsack ...

20001220BuchQuantitative stability in stochastic programming The method of probability metricsQuantitative stability of optimal values and solution sets to stochastic programming problems is studied when the underlying probability distribution varies in some metric space of probability measures. We give conditions ...

20000321BuchRandom lsc functions ScalarizationRandom lsc (lower semicontinuous) functions can be indentified with a vectorvalued random variable by means of an appropriate scalarization. It is shown that stationarity, ergodicity and independence properties are preserved ...

20000207BuchRandom lsc functions An ergodic theoremAn ergodic theorem for random lsc functions is obtained by relying on a (novel) 'scalarization' of such functions. In the process, Kolmogorov's extension theorem for randon lsc functions is established. Applications to ...

20000327BuchRobust path choice in networks with failures The problem of adaptive routing in a network with failures is considered. The network may be in one of finitely many states characterized by different travel times along the arcs, and transitions between the states occur ...

20000814BuchScenario reduction in stochastic programming: An approach using probability metrics Given a convex stochastic programming problem with a discrete initial probability distribution, the problem of optimal scenario reduction is stated as follows: Determine a scenario subset of prescribed cardinality and a ...

20000131BuchStochastic programming by Monte Carlo simulation methods We consider in this paper stochastic programming problems which can be formulated as an optimization problem of an expected value function subject to deterministic constraints. We discuss a Monte Carlo simulation approach ...