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Introduction to Discrete Event Simulation and Agent-based Modeling - Voting Systems, Health Care, Military, and Manufacturing (Paperback, 2011 ed.)
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Introduction to Discrete Event Simulation and Agent-based Modeling - Voting Systems, Health Care, Military, and Manufacturing (Paperback, 2011 ed.)
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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.
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