{"title":"The Constraint Model Of Attrition","authors":"D. Hartley","doi":"10.1109/WSC.1989.718783","DOIUrl":"https://doi.org/10.1109/WSC.1989.718783","url":null,"abstract":"Helmbold demonstrated a relationship between a ratio containing initial force sizes and casualties, herein called the Helmbold ratio, and the initial force ratio in a large number of historical battles. This paper examines some of the complexity of the Helmbold ration using analytical nd simulation techniques and demonstrates that a constraint model of attrition captures some aspects of historical data. The effect that the constraint model would have on warfare modeling is uncertain. However, some speculation has been attempted concerning its use in large scale simulations.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124689384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Non-Uniform Random Number Generation: A Survey And Tutorial","authors":"J. Ahrens","doi":"10.1109/WSC.1989.718661","DOIUrl":"https://doi.org/10.1109/WSC.1989.718661","url":null,"abstract":"The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will concentrate on the most important distributions arising in simulation applications. The considered non-uniform distributions fall into two categories: continuous and discrete. In either class very efficient methods for sampling from general distributions are presented. Specific cases considered include the exponential, normal, gamma, beta and Cauchy distributions in the continuous, and Poisson, binomial and hypergeometric generators in the discrete category. In selecting suitable specific algorithms for each distribution we rejected the 'easiest' methods which are not fast enough. On the other hand, some of the most efficient generators are rather difficult to implement. The selected algorithms are almost as fast as these, but not too complex. Their Fortran versions are portable except for the employed basic (0, 1)-uniform generators for which, however, the user may substitute his or her own favorite. A number of the proposed methods are the author's recent developments. Some well-known alternatives will also be mentioned.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131340255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimating System Availability And Reliability","authors":"A. Goyal","doi":"10.1109/WSC.1989.718688","DOIUrl":"https://doi.org/10.1109/WSC.1989.718688","url":null,"abstract":"This paper deals with methods for constructing and solving large Markov chain models of computer system availability and reliability. A set of powerful high level modeling constructs is discussed that can be used to represent the failure and repair behavior of the components interactions. If time independent failure and repair rates are assumed then a time homogeneous continuous time Markov chain can be constructed automatically from the modeling constructs used to decribe the system. Since, the size of Markov chains grows exponentially with the number of components modeled, simulation appears to be a practical way for solving models of large systems. However, the standard simulation takes very long simulation runs to estimate availability and reliability measures because the system failure event is a rare event. Therefore, variance reduction techniques which can aid in computing rare-event probabilities quickly are of interest. Specifically, the Importance Sampling technique has been found to be most useful. The modeling language and the simulation methods discussed in this paper have been implemented in a program package called the System Availability Estimator (SAVE).","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130632978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Contrasting Distributed Simulation With Parallel Replication: A Case Study Of A Queuing Simulation On A Network Of Transputers","authors":"R. Rajagopal, J. Comfort","doi":"10.1109/WSC.1989.718750","DOIUrl":"https://doi.org/10.1109/WSC.1989.718750","url":null,"abstract":"As discrete event simulation programs become larger and more complex, the amount of computing power required for their execution is rapidly increasing. One way to achieve this power is by a employing a multiple processor network to run the simulation programs. Two approaches to the problem of assigning tasks to processors are described--environment partitioning distributed simulation, in which the tasks required to perform a simulation are assigned to processors in the network; and parallel replication, in which copies of the simulation program are assigned to processors and the results of their execution aggregated. A simulation of an M/M/c queuing system has been implemented on networks of two and three transputers, using each approach. Heidelberger's statistical efficiency and the stabilization time of the system are used as metrics. The parallel replications tended to stabilize faster, but the statistical efficiencies were not significantly different.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129710528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simulation Graph Duality: A World View Transformation For Simple Queueing Models","authors":"L. Schruben, E. Yücesan","doi":"10.1145/76738.76832","DOIUrl":"https://doi.org/10.1145/76738.76832","url":null,"abstract":"Planar graphs play an important role in real world applications, partly due to the fact that some practical problems can be efficiently solved for planar graphs while they are intractable for general graphs. Simulation Graph Models of simple queueing systems are planar graphs. Their geometric duals can then be constructed. In the context of queueing models, this dualization process represents a transformation from the event scheduling to the activity scanning world view in discrete event simulation. The so-called primal-dual pair of models provides an alternative but equivalent representation of these stochastic systems.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115641865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Likelihood Ratio Derivative Estimators For Stochastic Systems","authors":"P. Glynn","doi":"10.1145/76738.76785","DOIUrl":"https://doi.org/10.1145/76738.76785","url":null,"abstract":"This paper discusses Iikelihood--ratio--derivative estimation techniques for stochastic systems. After a brief review of the basic concepts, likelihood-ratio-derivative estimators are presented for the following classes of stochastic processes: time homogeneous discrete-time Markov chains, non-time-homogeneous discrete-time Markov chains, time-homogeneous continuous-time Markov chains, semi-Markov processes, non-time-homogeneous continuous-time Markov chains, and generalized semi-Markov processes.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114680242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MODSIM II - An Object Oriented Simulation Language For Sequential And Parallel Processors","authors":"Otis F. Bryan","doi":"10.1145/76738.76758","DOIUrl":"https://doi.org/10.1145/76738.76758","url":null,"abstract":"MODSIM II is an object-oriented general purpose and simulation language designed to work with both sequential and parallel processors. Its objects have both single and multiple inheritance. It has a single syntax that works across a variety of systems including main frames, work stations and PC's. A parallel version is currently under development on the BBN Butterfly parallel computer under the Time Warp operating system. MODSIM II is based on the syntax of Modula-2. The majority of statements are identical with those in Modula-2. It has a few additional constructs that let the user write discrete process simulations. MODSIM II has built-in object oriented constructs, including single and multiple inheritance, data abstraction and information hiding. In addition, it supports separate compilation. This makes it useful for large projects. It contains interactive dynamic graphics to improve input and output.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127260580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Simulation Process: Avoiding The Problems And Pitfalls","authors":"R. Sadowski","doi":"10.1145/76738.76747","DOIUrl":"https://doi.org/10.1145/76738.76747","url":null,"abstract":"This tutorial will present an approach to conducting a simulation project that will aid in avoiding many common problems and pitfalls. The presentation will provide recommendations on how to scope the project, develop a functional specification, formulate and construct the model, verify and validate, collect data, document the work and perform the required analysis. The intent is to provide the novice simulation modeler with proven techniques for conducting a successful simulation project. A variety of case studies will be presented during the tutorial to illustrate both the right and wrong ways to conduct a project.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123006388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Selecting Simulation Software For Manufacturing Applications","authors":"A. Law, S. Haider","doi":"10.1145/76738.76742","DOIUrl":"https://doi.org/10.1145/76738.76742","url":null,"abstract":"The number of simulation packages available for performing manufacturing analyses has grown tremendously during the past five years, making it increasingly more difficult for an analyst to choose simulation software for a particular application. In this paper, we present a set of features which should be considered when evaluating simulation software and also a four-step selection strategy.","PeriodicalId":319104,"journal":{"name":"1989 Winter Simulation Conference Proceedings","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1989-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121903301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}