A New Approach to Simulating Stable Stochastic Systems: 1 - General Multi-Server Queues

A New Approach to Simulating Stable Stochastic Systems: 1 - General Multi-Server Queues PDF Author: Michael A. Crane
Publisher:
ISBN:
Category :
Languages : en
Pages : 46

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Book Description
A new technique is introduced for analyzing simulations of stochastic systems in the steady state. From the viewpoint of classical statistics, questions of simulation run duration and of starting and stopping simulations are addressed. This is possible because of the existence of a random grouping of observations which produces independent identically distributed blocks from the start of the simulation. The analysis is presented in the context of the general multi-server queue, with arbitrarily distributed inter-arrival and service times. In this case, it is the busy period structure of the system which produces the grouping mentioned above. Numerical illustrations are given for the M/M/1 queue.

A New Approach to Simulating Stable Stochastic Systems: 1 - General Multi-Server Queues

A New Approach to Simulating Stable Stochastic Systems: 1 - General Multi-Server Queues PDF Author: Michael A. Crane
Publisher:
ISBN:
Category :
Languages : en
Pages : 46

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Book Description
A new technique is introduced for analyzing simulations of stochastic systems in the steady state. From the viewpoint of classical statistics, questions of simulation run duration and of starting and stopping simulations are addressed. This is possible because of the existence of a random grouping of observations which produces independent identically distributed blocks from the start of the simulation. The analysis is presented in the context of the general multi-server queue, with arbitrarily distributed inter-arrival and service times. In this case, it is the busy period structure of the system which produces the grouping mentioned above. Numerical illustrations are given for the M/M/1 queue.

Efficient Estimators for Simulated Queueing Systems

Efficient Estimators for Simulated Queueing Systems PDF Author: Averill M. Law
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 108

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Book Description


Queueing Theory 1

Queueing Theory 1 PDF Author:
Publisher: John Wiley & Sons
ISBN: 1119755425
Category : Mathematics
Languages : en
Pages : 336

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Book Description
The aim of this book is to reflect the current cutting-edge thinking and established practices in the investigation of queueing systems and networks. This first volume includes ten chapters written by experts well-known in their areas. The book studies the analysis of queues with interdependent arrival and service times, characteristics of fluid queues, modifications of retrial queueing systems and finite-source retrial queues with random breakdowns, repairs and customers’ collisions. Some recent tendencies in the asymptotic analysis include the average and diffusion approximation of Markov queueing systems and networks, the diffusion and Gaussian limits of multi-channel queueing networks with rather general input flow, and the analysis of two-time-scale nonhomogenous Markov chains using the large deviations principle. The book also analyzes transient behavior of infinite-server queueing models with a mixed arrival process, the strong stability of queueing systems and networks, and applications of fast simulation methods for solving high-dimension combinatorial problems.

Second National Conference on Management Science and Practice, March 9-11, 2007

Second National Conference on Management Science and Practice, March 9-11, 2007 PDF Author:
Publisher: Allied Publishers
ISBN: 9788184243048
Category : Operations research
Languages : en
Pages : 316

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Book Description
Papers presented at the conference held at Indian Institute of Technology, Madras in 2007.

Simulation and the Monte Carlo Method

Simulation and the Monte Carlo Method PDF Author: Reuven Y. Rubinstein
Publisher: John Wiley & Sons
ISBN: 1118210522
Category : Mathematics
Languages : en
Pages : 331

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Book Description
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.

Monte Carlo

Monte Carlo PDF Author: George Fishman
Publisher: Springer Science & Business Media
ISBN: 1475725531
Category : Mathematics
Languages : en
Pages : 721

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Book Description
Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.

Proceedings

Proceedings PDF Author:
Publisher:
ISBN:
Category : Digital computer simulation
Languages : en
Pages : 874

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Book Description


Current Issues in Computer Simulation

Current Issues in Computer Simulation PDF Author: Nabil R. Adam
Publisher: Academic Press
ISBN: 1483258033
Category : Reference
Languages : en
Pages : 313

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Book Description
Current Issues in Computer Simulation is a collection of papers dealing with computer simulation languages, statistical aspects of simulation, linkage with optimization and analytical models, as well as theory and application of simulation methodology. Some papers explain the General Purpose Simulation System (GPSS), a programming package incorporating a language to simulate discrete systems; and the SIMSCRIPT, a general-purpose simulation language using English commands, for example, FORTRAN. Another simulation language is the General Activity Simulation Program (GASP), providing for an organizational structure to build models to simulate the dynamic performance of systems on a digital computer. Other papers discuss simulation models of real systems, including corporate simulation models, multistage consumer choice process, determination of maximum occupancy for hospital facilities, and the juvenile court system. Many computer simulations are statistical sampling experiments performed on a model of the system under investigation. Other papers discuss some of the variables involved in the statistical design and analysis of simulation experiments such as variance reduction techniques, generation of random variates, and experimental layout. For example, one application simulates inventory systems when many items are stocked in various locations. The collection is suitable for programmers, computer engineers, businessmen, hospital administrators, schools officials, and depositories of huge volumes of information or data.

Naval Research Logistics Quarterly

Naval Research Logistics Quarterly PDF Author:
Publisher:
ISBN:
Category : Logistics, Naval
Languages : en
Pages : 732

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Book Description


Handbooks in Operations Research and Management Science: Simulation

Handbooks in Operations Research and Management Science: Simulation PDF Author: Shane G. Henderson
Publisher: Elsevier
ISBN: 0080464769
Category : Business & Economics
Languages : en
Pages : 693

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Book Description
This Handbook is a collection of chapters on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. The chapters are tightly focused and written by experts in each area. For the purpose of this volume "simulation refers to the analysis of stochastic processes through the generation of sample paths (realization) of the processes. Attention focuses on design and analysis issues and the goal of this volume is to survey the concepts, principles, tools and techniques that underlie the theory and practice of stochastic simulation design and analysis. Emphasis is placed on the ideas and methods that are likely to remain an intrinsic part of the foundation of the field for the foreseeable future. The chapters provide up-to-date references for both the simulation researcher and the advanced simulation user, but they do not constitute an introductory level 'how to' guide. Computer scientists, financial analysts, industrial engineers, management scientists, operations researchers and many other professionals use stochastic simulation to design, understand and improve communications, financial, manufacturing, logistics, and service systems. A theme that runs throughout these diverse applications is the need to evaluate system performance in the face of uncertainty, including uncertainty in user load, interest rates, demand for product, availability of goods, cost of transportation and equipment failures.* Tightly focused chapters written by experts* Surveys concepts, principles, tools, and techniques that underlie the theory and practice of stochastic simulation design and analysis* Provides an up-to-date reference for both simulation researchers and advanced simulation users