A computationally efficient method for selecting a split questionnaire design

An Efficient Method for Selecting a Reliable Path under Uncertainty Conditions

In a network that has the potential to block some paths, choosing a reliable path, so that its survival probability is high, is an important and practical issue. The importance of this issue is very considerable in critical situations such as natural disasters, floods and earthquakes. In the case of the reliable path, survival or blocking of each arc on a network in critical situations is an un...

Method for computationally efficient design of dielectric laser accelerator structures.

Dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the...

Computationally Efficient Methods for Selecting Among Mixtures of Graphical Models

We describe computationally efficient methods for Bayesian model selection. The methods select among mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs), and can be applied to data sets in which some of the random variables are not always observed. The model-selection criterion that we consider is the posterior probability of the model (structure) ...

Design and Estimation for Split Questionnaire Surveys

COMPUTATIONALLY EFFICIENT OPTIMUM DESIGN OF LARGE SCALE STEEL FRAMES

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...