Adaptive importance sampling techniques are widely known for the Gaussian setting of Brownian driven diffusions. In this work, we want to extend them to jump processes. Our approach relies on a change of the jump intensity combined with the standard exponential tilting for the Brownian motion....

One of the challenges faced by liner operators today is to effectively operate empty containers in order to meet demand and to reduce inefficiency in an uncertain environment. To incorporate uncertainties in the operations model, we formulate a two-stage stochastic programming model with random...

We consider the problem of determining the minimal requirement one must establish in order to meet a series of future random payments. It is shown in a very general setting that this problem can be recast as a chance constrained model and how the technique of Sample Average Approximation can be...

<Para ID="Par1">Recent years have seen growing interest in coherent risk measures, especially in Conditional Value-at-Risk (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\mathrm {CVaR}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi mathvariant="normal">CVaR</mi> </math> </EquationSource> </InlineEquation>). Since <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$\mathrm {CVaR}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi mathvariant="normal">CVaR</mi> </math> </EquationSource> </InlineEquation> is a convex function, it is suitable as an objective for optimization problems when we desire to minimize risk. In the...</equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></para>

In this paper, we consider a class of two-stage stochastic optimization problems arising in the protection of vital arcs in a critical path network. A project is completed after a series of dependent tasks are all finished. We analyze a problem in which task finishing times are uncertain but can...

This paper considers a multicomponent, multiproduct periodic-review assemble-to-order (ATO) system that uses an independent base-stock policy for inventory replenishment. Product demands in each period are integer-valued correlated random variables, with each product being assembled from...

This work proposes a two-stage stochastic optimization model to maximize the expected profit and simultaneously minimize carbon emissions of a dual-feedstock lignocellulosic-based bioethanol supply chain (LBSC) under uncertainties in supply, demand and prices. The model decides the optimal...

Conditional value at risk (CVaR) has been widely used as a risk measure in finance. When the confidence level of CVaR is set close to 1, the CVaR risk measure approximates the extreme (worst scenario) risk measure. In this paper, we present a quantitative analysis of the relationship between the...

We present a novel hybrid method, swarm intelligence based sample average approximation (SIBSAA), for solving the capacitated reliable facility location problem (CRFLP). The CRFLP extends the well-known capacitated fixed-cost facility problem by accounting for the unreliability of facilities....