Open AccessBook
Simulation Modeling and Analysis
Averill M. Law,W. David Kelton +1 more
TLDR
The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.Abstract:
From the Publisher:
This second edition of Simulation Modeling and Analysis includes a chapter on "Simulation in Manufacturing Systems" and examples. The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering,business,computer science and operations research.read more
Citations
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Proceedings ArticleDOI
Kriging metamodeling in constrained simulation optimization: an explorative study
TL;DR: The results of these experiments indicate that Kriging offers opportunities for solving constrained optimization problems in stochastic simulation; future research will focus on further refining the methodology.
Book ChapterDOI
Ranking and Selection: Efficient Simulation Budget Allocation
TL;DR: This chapter presents algorithms that are derived from Bayesian and related conceptual frameworks to provide empirically effective performance for the ranking and selection problem and motivate the optimal computing budget allocation algorithm and expected value of information approaches.
Proceedings ArticleDOI
Simulation of the Internet of Things
TL;DR: It is claimed that agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches are needed, together with multi-level simulation, which provide means to perform highly detailed simulations, on demand.
Journal ArticleDOI
Probability Distribution Functions for Construction Simulation
TL;DR: The research validated previous warnings about the influence of the class interval decision on the selection of a distribution function when the chi-square fitting test is utilized and addressed the reliability of goodness-of-fit tests when dealing with large data sets.
Book Chapter
System Dynamics Modeling: Validation for Quality Assurance
TL;DR: The issue of model validation is treated as a means of assuring high-quality models and it is interjected that validity is not the only criterion of model quality, the other criteria being parsimony, ease-of-use, practicality, importance, etc.