- Full Description 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 optimiza