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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
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Monte Carlo and Quasi-Monte Carlo Sampling
TL;DR: The Monte Carlo method has been used in many applications, e.g., for algebra, beyond numerical integration, this article, and for error and variance analysis for Halton sequences.
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Empirical Validation of Agent-Based Models: Alternatives and Prospects
TL;DR: This paper addresses a set of methodological problems arising in the empirical validation of agent-based (AB) economics models and discusses how these are currently being tackled and gives rise to a novel taxonomy that captures the relevant dimensions along which AB modellers differ.
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Operations management research methodologies using quantitative modeling
Jwm Will Bertrand,JC Jan Fransoo +1 more
TL;DR: The methodology of quantitative model‐driven empirical research offers a great opportunity for operations management researchers to further advance theory and build on learnings from operations research and operations management research from the past decades.
Journal ArticleDOI
Modeling impacts of process architecture on cost and schedule risk in product development
TL;DR: This paper integrates several important characteristics of PD processes into a single model, highlighting the effects of varying process architecture and yielding several managerial insights, including: how rework cascades through a PD process, trading off cost and schedule risk, interface criticality, and occasions for iterative overlapping.
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A taxonomy of model structures for economic evaluation of health technologies
TL;DR: A new taxonomy of model structures is developed, based on key requirements, including output requirements, the population size, and system complexity, for modelling infectious diseases and systems with constrained resources.