Motivated by the challenges encountered in sawmill production planning, we study a multi-product, multi-period production planning problem with uncertainty in the quality of raw materials and consequently in processes yields, as well as uncertainty in products demands. As demand and yield own different uncertain natures, they are modeled separately and then integrated. Demand uncertainty is con...

This paper presents novel techniques for timing yield optimization and for yield estimation in the presence of large statistical process variations in integrated circuits. The techniques are based on our generalization of the logical effort delay model to circuits with stochastic parameter variations. In the spirit of the standard logical effort formalism, the stochastic gate delay model we pro...

Performance/dependability evaluation via modeling results in fast and economic system development. Traditionally, simulations have been used to evaluate realistic systems but do not yield exact results. Analytic solution methods can yield exact results, but can su er from the state-space explosion problem. A reduced base model construction technique for stochastic activity networks, which explo...

We describe quantum-field-theoretical (QFT) techniques for mapping quantum problems onto c-number stochastic problems. This approach yields results which are identical to phase-space techniques [C.W. Gardiner, Quantum Noise (1991)] when the latter result in a Fokker-Planck equation for a corresponding pseudo-probability distribution. If phase-space techniques do not result in a Fokker-Planck eq...

here in, an application of a new seismic inversion algorithm in one of iran’s oilfields is described. stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. this method integrates information from different data sources with different scales, as prior informat...

Manufactures often rely on different types of long term contracts with established suppliers to procure goods often involving delivery lead times; however, the emergence of online B2B markets provides an additional procurement flexibility. Manufacturers can interact directly with the market either through spot transactions or claims contingent on commodity prices. In particular, we explore the ...

Optimal experimental design (OED) seeks experiments expected to yield the most useful data for some purpose. In practical circumstances where experiments are time-consuming or resource-intensive, OED can yield enormous savings. We pursue OED for nonlinear systems from a Bayesian perspective, with the goal of choosing experiments that are optimal for parameter inference. Our objective in this co...

We study server scheduling in multiclass service systems under stochastic uncertainty in the customer arrival volumes. Common practice in such systems is to first identify staffing levels, and then determine schedules for the servers that cover these targets. We propose a new stochastic integer programming model that integrates these two decisions, which can yield lower scheduling costs by expl...

research interests include evolution and learning in games and the economics of technological standardization. Abstract We survey three classes of models from evolutionary game theory which make history independent predictions: stochastic stability, stochastic stability with local interaction, and cheap talk. We argue that of the three, only local interaction models yield credible history indep...

Consistent stochastic orders of processing times and objective functions yield optimal policies in many stochastic scheduling problems. When these orders fail to hold, however, finding optimal values may be difficult. In this paper, we show how to bound these values in general situations including problems with unreliable machines and tardiness-based objectives.