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This research aims to develop a hybrid methodology to support lean management to improve the sustainability of the construction phase. The combination of Value Stream Mapping and Process-based Life Cycle Assessment is enhanced by integrating with simulation methods to consider the environmental performance of the construction phase. Data from predefined process patterns, Life Cycle Assessment databases, and Building Information Modelling models, are used as input to the simulation-based Value Stream Mapping model. This methodology will enable an examination of the environmental impact of particular situations as what-if scenarios, during the planning and construction phases, without compromising the achievement of the construction process objectives.
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.
The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.
Rapidly changing market, technological, and organizational environments are forcing government and private sector enterprises to improve services and transform processes. Employing a case study approach, the Enterprise Dynamics Sourcebook presents frameworks and analytical models of the enterprise as a complex system to improve your understanding of its dynamic elements and their interactions. Illustrating the transformation environments and the evolution of methods required to address emerging challenges, this sourcebook is the product of MITRE-sponsored research on enterprise dynamics and the range of applications pertaining to enterprise transformation programs. It explains how to address the complexities involved with the coordination of policies, organizations, economics, and technology (POET) in operational strategies and processes. It also: Presents qualitative and quantitative data-analytic methods including process workflow, systems dynamics, and highly optimized tolerance-inspired models of SoSE processes Features Bayesian probability and state-space transition methods to address uncertainties in the controlled, influenced, and uncontrolled aspects of enterprise dynamics Explains how to use hybrid multi-scale modeling coupled with enterprise architecture to support decision making in the design, acquisition, and management of complex transformation efforts Outlines methods applicable in the national security, aviation, nuclear waste processing, international commerce, energy and materials, and healthcare sectors of the U.S. economy The structures and concepts covered in this book will be useful to managers and technical staff in government entities as well as private sector enterprises with significant operational and regulatory interaction with government entities. The enterprise dynamics methods discussed can help in the advancement of systems engineering practices at the enterprise level and also enable the enterprise systems engineering and architecting (ESE/A) process. Filled with examples, the text provides the understanding of the qualitative and quantitative data-analytic methods required to reduce risk and failure rates and enable your organization to operate effectively in today’s complex and ever-changing environment.
"This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. There is substantial attention to programming, output analysis, pseudo-random number generation and modelling and these sections are quite thorough. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions." --ISI Short Book Reviews, 22:2, August 2002
This book constitutes the proceedings of the 12th IFIP TC 8 International Conference, CISIM 2013, held in Cracow, Poland, in September 2013. The 44 papers presented in this volume were carefully reviewed and selected from over 60 submissions. They are organized in topical sections on biometric and biomedical applications; pattern recognition and image processing; various aspects of computer security, networking, algorithms, and industrial applications. The book also contains full papers of a keynote speech and the invited talk.
Over the last decades Discrete Event Simulation has conquered many different application areas. This trend is, on the one hand, driven by an ever wider use of this technology in different fields of science and on the other hand by an incredibly creative use of available software programs through dedicated experts. This book contains articles from scientists and experts from 10 countries. They illuminate the width of application of this technology and the quality of problems solved using Discrete Event Simulation. Practical applications of simulation dominate in the present book. The book is aimed to researchers and students who deal in their work with Discrete Event Simulation and which want to inform them about current applications. By focusing on discrete event simulation, this book can also serve as an inspiration source for practitioners for solving specific problems during their work. Decision makers who deal with the question of the introduction of discrete event simulation for planning support and optimization this book provides a contribution to the orientation, what specific problems could be solved with the help of Discrete Event Simulation within the organization.
During the last two decades, increase in electricity demand and environmental concern resulted in fast growth of power production from renewable sources. Wind power is one of the most efficient alternatives. Due to rapid development of wind turbine technology and increasing size of wind farms, wind power plays a significant part in the power production in some countries. However, fundamental differences exist between conventional thermal, hydro, and nuclear generation and wind power, such as different generation systems and the difficulty in controlling the primary movement of a wind turbine, due to the wind and its random fluctuations. These differences are reflected in the specific interaction of wind turbines with the power system. This book addresses a wide variety of issues regarding the integration of wind farms in power systems. The book contains 14 chapters divided into three parts. The first part outlines aspects related to the impact of the wind power generation on the electric system. In the second part, alternatives to mitigate problems of the wind farm integration are presented. Finally, the third part covers issues of modeling and simulation of wind power system.
Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. - Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring - Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making - Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis
Offers comprehensive coverage of discrete-event simulation, emphasizing and describing the procedures used in operations research - methodology, generation and testing of random numbers, collection and analysis of input data, verification of simulation models and analysis of output data.