WSC

GPSS(General Purpose Simulation System) is a simulation programming language whose use greatly eases the task of building computer models for discrete-event simulations. (A discrete event simulation is one in which the state of the system being ...

Since World War II system modeling has played an increasingly important role in the analysis of complex systems in both the private and public sectors. In the broadest sense, a model may be considered to be a representation of reality without the ...

The crucial phase in simulating a real-world system is the formulation and development of a credible model of that system. This workshop examines selected phases of model development, including (1) development of flow charts describing the mathematical-...

Early effort in a simulation study is concerned with defining the system to be modeled and describing it in terms of logic flow diagrams and functional relationships. But eventually one is faced with the problem of describing the model in a language ...

This presentation will explore some of the fundamental characteristics of discrete-event simulation modeling, examine the utility of the simulation tool on the basis of industrial experience, discuss the strengths and weaknesses of simulation, and give ...

Nearly two thousand firms in the United States, Canada, and Mexico are either using, developing, or experimenting with some form of corporate planning model. Computer based planning models represent an attempt to describe the complex inter-relationships ...

GASP is a simulation language that provides an organizational structure to build models that can be used to simulate the dynamic performance of systems on a digital computer. The organizational structure of GASP allows the variables that define system ...

Simulation languages typically are designed to substantially reduce the time and cost required to build simulation models by automatically providing commonly needed facilities, such as statistics gathering, a timing mechanism, random deviates, powerful ...

Technical details of various approaches to the analysis of simulation output are presented in other sessions of this conference and have been the topic of previous Winter Simulation Conference sessions. This tutorial will include an introduction to many ...

This paper remarks upon some issues involved in evaluating the “randomness” of numerical sequences. The question of how much to test is addressed, particularly with respect to pseudorandom generators. Historical failures of seemingly random sequences ...

Methods of modelling probabilistic components which are not adequately represented by the standard continuous distributions (such as normal, gamma, and Weibull) are surveyed. The methods are categorized as systems of distributions, approximations to the ...

“Ranking and selection” procedures were developed for use in situations where the experimenter's goal is to “select the best” (selection) or to “rank competing alternatives” (ranking). These are typical goals when a simulation study is performed, often ...

The performance of many if not most real-life systems which are simulated depends on two or more factors which can be set at various “levels.” In order to understand the behavior of such a system the experimenter must conduct a factorial experiment in ...

In many simulation studies there are available several alternatives and the experimenter is simulating in order to choose which one is best with regard to certain specified criteria. Once an alternative has been selected, people may raise the question: “...

In this paper, the origin of selection and ranking problems is discussed. Then the two basic approaches to the selection problem - the indifference zone approach and the subset selection approach - are reviewed briefly. As an application, Gupta's subset ...

When k alternatives are simulated (e.g. in a study to find which one optimizes the performance of some real or planned system) it is not rare for multiple criteria to be employed (i.e., several system responses are of interest and no simple combination ...

This article reviews the practical aspects of several nonparametric subset selection rules useful in block design problems, and discusses advantages and disadvantages of these methods. The populations are assumed stochastically ordered by the parameter ...

A nonparametric formulation is set up for selecting the best one of k populations where best is defined as the one with the smallest inter(α,β)-range; here inter(α,β)-range is a measure of dispersion defined by the difference of the β^th quantile and the ...

Management Scientists and systems analysts often wish to find the values of input variables which optimize (maximize or minimize) some function of system performance. If the system can be described analytically, mathematical programming is used to find ...

This paper describes an optimization module which can be added to the GASP IV software package to provide automated optimization of a set of user defined decision variables. The optimization procedure is a variation of the Hooke-Jeeves pattern search ...

This paper examines several procedures for optimizing simulation models having controllable input variables x_i,i = 1,...,n and yielding responses n_j,j = 1,...,m. This problem is often formulated as a constrained optimization problem, or it can be ...

One major problem in combinatorial theory is to find a combination that will optimize a given objective function. However, for many real problems even with moderate requirements, no algorithm exists which can find an optimum in a livable span of time. ...

Control variables are presented which reduce the variance of estimators of steady state response characteristics in the simulation of a broad class of closed queueing networks. Statistical aspects of applying control variables in this context are ...

This paper discusses a procedure for interval estimation of the mean @@@@ of a correlated binary (0,1) sequence. The method assumes that the sequence is strictly stationary and that a particular string of m binary digits is a recurrent event in the ...

Simulators frequently wish to estimate parameters of the limiting distribution of stable stochastic processes. Several new methods for reducing the variance of such estimates will be proposed and discussed. The methods are applicable to regenerative ...

Most of the statistical simulation literature is concerned with steady-state simulations. That is, a simulation where the quantity to be estimated is defined as a limit as time (or the number of customers) goes to infinity. For example, the regenerative ...

Formulas are derived for the variance of sample means associated with finite state Markov processes. Results are presented to illustrate the use of the formulas for example processes. The formulas can be used to evaluate proposed statistical methods for ...

A technique for generating confidence intervals on the common expectation of a sequence of correlated random variables is developed. The sequence is modelled as a covariance stationary process. In this situation the variance of the sample mean is ...

We consider the efficient estimation of mean delay in queue, d, mean wait in system, w, time average number in queue, Q, and time average number in system, L, for simulated queueing systems. We prove for the GI/G/s queue that it is more efficient to ...

An analysis of the effect of two alternative inventory selection rules is performed to determine their effect on both cost per flight and schedule reliability for the planned Space Shuttle Program.

The major objective of the Space Shuttle Program is to ...