Isbn: 9780857291387 - Introduction to Discrete Event Simulation and Agent-based Modeling: Voting Systems, Health Care, Military, and Manufacturing (22 results)

Condition: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2011.

hardcover. Condition: Very Good. Cover and edges may have some wear.

hardcover. Condition: Fine.

hardcover. Condition: Good. 2011th Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Condition: New. pp. 228.

Condition: New. pp. 228 Illus.

Condition: New. pp. 228.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. In English.

Condition: New.

Hardback. Condition: New. 2011 ed. Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include. Definition - The reader will learn how to plan a project and communicate using a charter. . Input analysis - The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. . Simulation - The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. . Output analysis - The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. . Decision support - Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.…

Condition: As New. Unread book in perfect condition.

Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Hardback. Condition: New. 2011 ed. Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include. Definition - The reader will learn how to plan a project and communicate using a charter. . Input analysis - The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. . Simulation - The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. . Output analysis - The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. . Decision support - Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.…

Condition: new. Questo è un articolo print on demand.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include:- Definition - The reader will learn how to plan a project and communicate using a charter.- Input analysis - The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data.- Simulation - The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods.- Output analysis - The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations.- Decision support - Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention.Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals. 215 pp. Englisch.…

Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides readers with the ability to competently apply technology that is considered key in many industries and branches of governmentGives a case study of the author s work on the 2008 USA presidential election processContains numerous pro.…

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.