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Advancing the Frontiers of Simulation
This Festschrift honors George Samuel Fishman, one of the founders of the eld of computer simulation and a leader of the disciplines of operations research and the management sciences for the past ve decades, on the occasion of his seventieth birthday. The papers in this volume span the theory, methodology, and application of computer simulation. The lead article is appropriately titled “George Fishman’s Professional Career.” In this article we discuss George’s contributions to operations research and the m- agement sciences, with special emphasis on his role in the advancement of the eld of simulation since the 1960s. We also include a brief personal biography together with comments...
The Effects of the Lowered Maximum Speed Limit and Fuel Shortage on Highway Safety in North Carolina
" ... accidents decreased 9.5 percent, fatal accidents decreased 21.0 percent, and injury accidents decreased 12.0 percent in North Carolina."--Abstract
The Simulation Metamodel
Researchers develop simulation models that emulate real-world situations. While these simulation models are simpler than the real situation, they are still quite complex and time consuming to develop. It is at this point that metamodeling can be used to help build a simulation study based on a complex model. A metamodel is a simpler, analytical model, auxiliary to the simulation model, which is used to better understand the more complex model, to test hypotheses about it, and provide a framework for improving the simulation study. The use of metamodels allows the researcher to work with a set of mathematical functions and analytical techniques to test simulations without the costly running and re-running of complex computer programs. In addition, metamodels have other advantages, and as a result they are being used in a variety of ways: model simplification, optimization, model interpretation, generalization to other models of similar systems, efficient sensitivity analysis, and the use of the metamodel's mathematical functions to answer questions about different variables within a simulation study.
Private Wealth
An in-depth examination of today's most important wealth management issues Managing the assets of high-net-worth individuals has become a core business specialty for investment and financial advisors worldwide. Keeping abreast of the latest research in this field is paramount. That's why Private Wealth, the inaugural offering in the CFA Institute Investment Perspectives series has been created. As a sister series to the globally successful CFA Institute Investment Series, CFA Institute and John Wiley are proud to offer this new collection. Private Wealth presents the latest information on lifecycle modeling, asset allocation, investment management for taxable private investors, and much more...
Record - Society of Actuaries
Papers presented at regional and annual meetings of the Society of Actuaries.
Process Simulation Using WITNESS
Teaches basic and advanced modeling and simulation techniques to both undergraduate and postgraduate students and serves as a practical guide and manual for professionals learning how to build simulation models using WITNESS, a free-standing software package. This book discusses the theory behind simulation and demonstrates how to build simulation models with WITNESS. The book begins with an explanation of the concepts of simulation modeling and a “guided tour” of the WITNESS modeling environment. Next, the authors cover the basics of building simulation models using WITNESS and modeling of material-handling systems. After taking a brief tour in basic probability and statistics, simulati...
Optimal Two Stage Procedures for Estimating Functions of Parameters in Reliability and Queueing Models
In this dissertation, we consider the problem of estimating functions of parameters found in reliability and queueing models. The problem is to allocate a fixed sampling budget among the populations with the goal of minimizing the mean squared error (MSF) of the estimator. We consider the reliability model with three components such that the probability the system works is f(u1,u2,u3) = u1(u2+u3), and the mean waiting time of the M/G/I queue. For each of these models, we consider a set of sample sizes referred to as a first-allocation procedure which minimizes the first-order approximation to the MSE. Since the first-order allocation procedure depends on the unknown parameters in the model, ...
