This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

This paper surveys verification and validation of models, especially simulation models in operations research. For verification it discusses 1) general good programming practice (such as modular programming), 2) checking intermediate simulation outputs through tracing and statistical testing per module, 3) statistical testing of final simulation outputs against analytical results, and 4) animation. For validation it discusses 1) obtaining real-worl data, 2) comparing simulated and real data through simple tests such as graphical, Schruben-Turing, and t tests, 3) testing whether simulated and real responses are positively correlated and moreover have the same mean, using two new statistical procedures based on regression analysis, 4) sensitivity analysis based on design of experiments and regression analysis, and risk or uncertainty analysis based on Monte Carlo sampling, and 5) white versus black box simulation models. Both verification and validation require good documentation, and are crucial parts of assessment, credibility, and accreditation. A bibliography with 61 references is included.

Verification and validation of simulation models

Coloured Petri Nets (CPNs) is a language for the modelling and validation of systems in which concurrency, communication, and synchronisation play a major role. Coloured Petri Nets is a discrete-event modelling language combining Petri nets with the functional programming language Standard ML. Petri nets provide the foundation of the graphical notation and the basic primitives for modelling concurrency, communication, and synchronisation. Standard ML provides the primitives for the definition of data types, describing data manipulation, and for creating compact and parameterisable models. A CPN model of a system is an executable model representing the states of the system and the events (transitions) that can cause the system to change state. The CPN language makes it possible to organise a model as a set of modules, and it includes a time concept for representing the time taken to execute events in the modelled system. CPN Tools is an industrial-strength computer tool for constructing and analysing CPN models. Using CPN Tools, it is possible to investigate the behaviour of the modelled system using simulation, to verify properties by means of state space methods and model checking, and to conduct simulation-based performance analysis. User interaction with CPN Tools is based on direct manipulation of the graphical representation of the CPN model using interaction techniques, such as tool palettes and marking menus. A license for CPN Tools can be obtained free of charge, also for commercial use.

/pdf/coloured-petri-nets-and-cpn-tools-for-modelling-and-j2qro6d905.pdf

Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas, contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampling, it reviews sequentialized and customized designs. It ends with topics for future research.

/pdf/kriging-metamodeling-in-simulation-a-review-2hj4mjqeb7.pdf

Kriging Metamodeling in Simulation: A Review

Objects. The ~ b s t rac t ~ b j ect forms the fundamental base class for the entire design and all other classes are derived from this base class. The Abstract Object class defines and characterizes all the essential properties every class in this 404 OBJECT-ORIENTED SIMULATION

Handbook of Simulation

This introduction begins with an example of simulation done by hand. Modeling concepts in simulation are then introduced based on the example. Next, the advantages and disadvantages of simulation are discussed. The introduction ends with a discussion of the steps in a simulation study.

Introduction to simulation

Principles of Simulation

In this article, we introduce the reader to discrete-event simulation. The concepts of system and model, system state, entities, attributes and delays are defined in the general context of simulation. Using these concepts, event-scheduling, process-interaction, and activity-scanning perspectives are briefly described. To demonstrate the use of the concepts, a discrete system is modeled using the event-scheduling perspective. Simulation languages are classified in terms of the type of system being modeled, the application level, and the perspective taken. The features of a simulation language are discussed. Lastly, basic information is provided about an assortment of discrete-event simulation languages.

/pdf/introduction-to-discrete-event-simulation-1je93xiurk.pdf

Introduction to discrete-event simulation

It has become a matter of survival that many companies improve their supply chain efficiency. This presents an opportunity for simulation. However, there are many challenges that must be overcome for simulation to be a contributor to play an effective role. Four contributors discuss the opportunities that they see for simulation to play a meaningful role in the area of supply chain management.

Jerry Banks

Papers

Handbook of Simulation

Introduction to simulation

Principles of Simulation

Introduction to discrete-event simulation

Panel session: opportunities for simulation in supply chain management