A Branch and Bound Method for Stochastic Global Optimization

A stochastic version of the branch and bound method is proposed for solving stochastic global optimization problems. The method, instead of deterministic bounds, uses stochastic upper and lower estimates of the optimal value of subproblems, to guide the partitioning process. Almost sure convergence of the method is proved and random accuracy estimates derived. Methods for constructing random bounds for stochastic global optimization problems are discussed. The theoretical considerations are illustrated with an example of a facility location problem

Generalization of a theorem of Gonchar

Let $X, Y$ be two complex manifolds, let $D\subset X,$ $G\subset Y$ be two nonempty open sets, let $A$ (resp. $B$) be an open subset of $\partial D$ (resp. $\partial G$), and let $W$ be the 2-fold cross $((D\cup A)\times B)\cup (A\times(B\cup G)).$ Under a geometric condition on the boundary sets $A$ and $B,$ we show that every function locally bounded, separately continuous on $W,$ continuous on $A\times B,$ and separately holomorphic on $(A\times G) \cup (D\times B)$ "extends" to a function continuous on a "domain of holomorphy" $\hat{W}$ and holomorphic on the interior of $\hat{W}.$Comment: 14 pages, to appear in Arkiv for Matemati

Configurations of Series-Parallel Networks with Maximum Reliability

The optimal design problem for networks with 3-state components is the following: select from a given class of networks with n components, each of which can he operative or experience an open-mode or a shorted-mode failure state, the network with maximum reliability. We present an algorithm for solving this problem in the case of 2-stage series-parallel networks, i.e., networks consisting of a number of series configurations linked in parallel or vice versa. For practically relevant network sizes (up to 100 components), the algorithm is fast

Forming peculiarities and manifestation of tectonic faults in soft rocks

Features of distribution of tectonic structures in soft rocks confirm the presence of horizontal tectonic forces in the formation of faults and are based on the manifestation of their morphological features. Linear dependences of the amplitude on the length of tectonic dislocation in the area of wedging were obtained as a result of mathematical processing of the experimental data. Actual position of the crossing lines of fault plane with the seam were considered while studying the distribution of co-fault fracturing. Analysis of the data confirms that the distribution of faulting has an undulating character. Analysis of observations showed that the deviation of the crossing line of fault plane with the seam from the middle line is subject to the normal law of random variable distribution. Thus, the studies and the obtained results allow planning mining operations assessing the utility while developing fault areas

Incorporating model uncertainty into optimal insurance contract design

In stochastic optimization models, the optimal solution heavily depends on the selected probability model for the scenarios. However, the scenario models are typically chosen on the basis of statistical estimates and are therefore subject to model error. We demonstrate here how the model uncertainty can be incorporated into the decision making process. We use a nonparametric approach for quantifying the model uncertainty and a minimax setup to find model-robust solutions. The method is illustrated by a risk management problem involving the optimal design of an insurance contract

Comfort-oriented control strategies for decentralized ventilation using co-simulation

Mechanical ventilation systems have acquired relevance in the past years in order to guarantee the hygrothermal comfort and indoor air quality (IAQ) in highly retrofitted residential buildings. The optimization of control strategies could provide a solution to this existing trade-off between energy efficiency, hygrothermal comfort and IAQ. In this publication, we propose a co-simulation approach (using EnergyPlus and Modelica) and a mathematical approximation of the discomfort of the occupant (namely, quadratic for relative humidity and exponential for CO2), and apply them to a demand controlled ventilation (DCV) scheme. Results show that this approach provides around 10% energy savings, while improving the thermal comfort, without compromising the humidity comfort or the IAQ. Finally, the developed functions could allow the control schemes to adapt to different occupant preferences, showing potential for future work

Known source detection predictions for higher order correlators

The problem addressed in this paper is whether higher order correlation detectors can perform better in white noise than the cross correlation detector for the detection of a known transient source signal, if additional receiver information is included in the higher order correlations. While the cross correlation is the optimal linear detector for white noise, additional receiver information in the higher order correlations makes them nonlinear. In this paper, formulas that predict the performance of higher order correlation detectors of energy signals are derived for a known source signal. Given the first through fourth order signal moments and the noise variance, the formulas predict the SNR for which the detectors achieve a probability of detection of 0.5 for any level of false alarm, when noise at each receiver is independent and identically distributed. Results show that the performance of the cross correlation, bicorrelation, and tricorrelation detectors are proportional to the second, fourth, and sixth roots of the sampling interval, respectively, but do not depend on the observation time. Also, the SNR gains of the higher order correlation detectors relative to the cross correlation detector improve with decreasing probability of false alarm. The source signal may be repeated in higher order correlations, and gain formulas are derived for these cases as well. Computer simulations with several test signals are compared to the performance predictions of the formulas. The breakdown of the assumptions for signals with too few sample points is discussed, as are limitations on the design of signals for improved higher order gain. Results indicate that in white noise it is difficult for the higher order correlation detectors in a straightforward application to achieve better performance than the cross correlation. © 1998 Acoustical Society of America