Applied Simulation And Optimization

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Modeling, Simulation, and Optimization of Supply Chains

Author : Ciro D'Apice
Publisher : SIAM
ISBN 13 : 0898717000
Total Pages : 209 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Modeling, Simulation, and Optimization of Supply Chains by : Ciro D'Apice

Download or read book Modeling, Simulation, and Optimization of Supply Chains written by Ciro D'Apice and published by SIAM. This book was released on 2010-07-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a state-of-the-art introduction to the mathematical theory of supply chain networks, focusing on those described by partial differential equations. The authors discuss modeling of complex supply networks as well as their mathematical theory, explore modeling, simulation, and optimization of some of the discussed models, and present analytical and numerical results on optimization problems. Real-world examples are given to demonstrate the applicability of the presented approaches. Graduate students and researchers who are interested in the theory of supply chain networks described by partial differential equations will find this book useful. It can also be used in advanced graduate-level courses on modeling of physical phenomena as well as introductory courses on supply chain theory.

Applied Simulation and Optimization 2

Author : Miguel Mujica Mota
Publisher : Springer
ISBN 13 : 3319558102
Total Pages : 286 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Applied Simulation and Optimization 2 by : Miguel Mujica Mota

Download or read book Applied Simulation and Optimization 2 written by Miguel Mujica Mota and published by Springer. This book was released on 2017-05-18 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on the author’s earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into the optimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.

Geometric Modelling, Numerical Simulation, and Optimization:

Author : Geir Hasle
Publisher : Springer Science & Business Media
ISBN 13 : 3540687831
Total Pages : 559 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Geometric Modelling, Numerical Simulation, and Optimization: by : Geir Hasle

Download or read book Geometric Modelling, Numerical Simulation, and Optimization: written by Geir Hasle and published by Springer Science & Business Media. This book was released on 2007-06-10 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume addresses the importance of mathematics for industry and society by presenting highlights from contract research at the Department of Applied Mathematics at SINTEF, the largest independent research organization in Scandinavia. Examples range from computer-aided geometric design, via general purpose computing on graphics cards, to reservoir simulation for enhanced oil recovery. Contributions are written in a tutorial style.

Handbook of Simulation Optimization

Author : Michael C Fu
Publisher : Springer
ISBN 13 : 1493913840
Total Pages : 400 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Handbook of Simulation Optimization by : Michael C Fu

Download or read book Handbook of Simulation Optimization written by Michael C Fu and published by Springer. This book was released on 2014-11-13 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.

Optimization, Simulation and Control

Author : Rentsen Enkhbat
Publisher : Springer Nature
ISBN 13 : 303141229X
Total Pages : 202 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Optimization, Simulation and Control by : Rentsen Enkhbat

Download or read book Optimization, Simulation and Control written by Rentsen Enkhbat and published by Springer Nature. This book was released on 2023-12-01 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume gathers selected, peer-reviewed works presented at the 7th International Conference on Optimization, Simulation and Control, ICOSC 2022, held at the National University of Mongolia, Ulaanbaatar, June 20–22, 2022. Topics covered include (but are not limited to) mathematical programming; network, global, linear, nonlinear, parametric, stochastic, and multi-objective optimization; control theory; biomathematics; and deep and machine learning, to name a few. Held every three years since 2002, the ICOSC conference has become a traditional gathering for experienced and young researchers in optimization and control to share recent findings in these fields and discuss novel applications in myriad sectors. Researchers and graduate students in the fields of mathematics, engineering, and computer science can greatly benefit from this book, which can also be enjoyed by advanced practitioners in research laboratories and the industry. The 2022 edition of the ICOSC conference was sponsored by the Mongolian Academy of Sciences, the National University of Mongolia and the German-Mongolian Institute for Resources and Technology.

Stochastic Simulation Optimization

Author : Chun-hung Chen
Publisher : World Scientific
ISBN 13 : 9814282642
Total Pages : 246 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Stochastic Simulation Optimization by : Chun-hung Chen

Download or read book Stochastic Simulation Optimization written by Chun-hung Chen and published by World Scientific. This book was released on 2011 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation.

Simulation-Based Optimization

Author : Abhijit Gosavi
Publisher : Springer
ISBN 13 : 1489974911
Total Pages : 530 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Simulation-Based Optimization by : Abhijit Gosavi

Download or read book Simulation-Based Optimization written by Abhijit Gosavi and published by Springer. This book was released on 2014-10-30 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Modeling, Simulation and Optimization

Author : Biplab Das
Publisher : Springer Nature
ISBN 13 : 9811598290
Total Pages : 802 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Modeling, Simulation and Optimization by : Biplab Das

Download or read book Modeling, Simulation and Optimization written by Biplab Das and published by Springer Nature. This book was released on 2021-03-17 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization, organized by National Institute of Technology, Silchar, Assam, India, during 3–5 August 2020. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy system and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.

Modeling, Simulation, and Optimization

Author : Pandian Vasant
Publisher : Springer
ISBN 13 : 3319705423
Total Pages : 133 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Modeling, Simulation, and Optimization by : Pandian Vasant

Download or read book Modeling, Simulation, and Optimization written by Pandian Vasant and published by Springer. This book was released on 2017-12-07 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume. Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016; Includes research into soft computing and its application in engineering and technology; Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.

Chemical Process Retrofitting and Revamping

Author : Gade Pandu Rangaiah
Publisher : John Wiley & Sons
ISBN 13 : 1119016304
Total Pages : 432 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Chemical Process Retrofitting and Revamping by : Gade Pandu Rangaiah

Download or read book Chemical Process Retrofitting and Revamping written by Gade Pandu Rangaiah and published by John Wiley & Sons. This book was released on 2016-01-29 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed book will be divided into three parts. The chapters in Part I provide an overview of certain aspect of process retrofitting. The focus of Part II is on computational techniques for solving process retrofit problems. Finally, Part III addresses retrofit applications from diverse process industries. Some chapters in the book are contributed by practitioners whereas others are from academia. Hence, the book includes both new developments from research and also practical considerations. Many chapters include examples with realistic data. All these feature make the book useful to industrial engineers, researchers and students.

Computing Tools for Modeling, Optimization and Simulation

Author : Manuel Laguna
Publisher : Springer Science & Business Media
ISBN 13 : 9780792377184
Total Pages : 330 pages
Book Rating : 4.3/5 (771 download)

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Book Synopsis Computing Tools for Modeling, Optimization and Simulation by : Manuel Laguna

Download or read book Computing Tools for Modeling, Optimization and Simulation written by Manuel Laguna and published by Springer Science & Business Media. This book was released on 1999-11-30 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing Tools for Modeling, Optimization and Simulation reflects the need for preserving the marriage between operations research and computing in order to create more efficient and powerful software tools in the years ahead. The 17 papers included in this volume were carefully selected to cover a wide range of topics related to the interface between operations research and computer science. The volume includes the now perennial applications of rnetaheuristics (such as genetic algorithms, scatter search, and tabu search) as well as research on global optimization, knowledge management, software rnaintainability and object-oriented modeling. These topics reflect the complexity and variety of the problems that current and future software tools must be capable of tackling. The OR/CS interface is frequently at the core of successful applications and the development of new methodologies, making the research in this book a relevant reference in the future. The editors' goal for this book has been to increase the interest in the interface of computer science and operations research. Both researchers and practitioners will benefit from this book. The tutorial papers may spark the interest of practitioners for developing and applying new techniques to complex problems. In addition, the book includes papers that explore new angles of well-established methods for problems in the area of nonlinear optimization and mixed integer programming, which seasoned researchers in these fields may find fascinating.

Applied Simulation

Author : Malcolm Beaverstock
Publisher :
ISBN 13 : 9780983231929
Total Pages : 432 pages
Book Rating : 4.2/5 (319 download)

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Book Synopsis Applied Simulation by : Malcolm Beaverstock

Download or read book Applied Simulation written by Malcolm Beaverstock and published by . This book was released on 2012-07-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Surrogates

Author : Robert B. Gramacy
Publisher : CRC Press
ISBN 13 : 1000766209
Total Pages : 560 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Surrogates by : Robert B. Gramacy

Download or read book Surrogates written by Robert B. Gramacy and published by CRC Press. This book was released on 2020-03-10 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than 200 full colour figures. • Includes many exercises to supplement understanding, with separate solutions available from the author. • Supported by a website with full code available to reproduce all methods and examples. The book is primarily designed as a textbook for postgraduate students studying GP regression from mathematics, statistics, computer science, and engineering. Given the breadth of examples, it could also be used by researchers from these fields, as well as from economics, life science, social science, etc.

Optimization Methods Applied to Power Systems

Author : Francisco G. Montoya
Publisher : MDPI
ISBN 13 : 3039211307
Total Pages : 382 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Optimization Methods Applied to Power Systems by : Francisco G. Montoya

Download or read book Optimization Methods Applied to Power Systems written by Francisco G. Montoya and published by MDPI. This book was released on 2019-07-26 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Modeling, Stochastic Control, Optimization, and Applications

Author : George Yin
Publisher : Springer
ISBN 13 : 3030254984
Total Pages : 593 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Modeling, Stochastic Control, Optimization, and Applications by : George Yin

Download or read book Modeling, Stochastic Control, Optimization, and Applications written by George Yin and published by Springer. This book was released on 2019-07-16 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects papers, based on invited talks given at the IMA workshop in Modeling, Stochastic Control, Optimization, and Related Applications, held at the Institute for Mathematics and Its Applications, University of Minnesota, during May and June, 2018. There were four week-long workshops during the conference. They are (1) stochastic control, computation methods, and applications, (2) queueing theory and networked systems, (3) ecological and biological applications, and (4) finance and economics applications. For broader impacts, researchers from different fields covering both theoretically oriented and application intensive areas were invited to participate in the conference. It brought together researchers from multi-disciplinary communities in applied mathematics, applied probability, engineering, biology, ecology, and networked science, to review, and substantially update most recent progress. As an archive, this volume presents some of the highlights of the workshops, and collect papers covering a broad range of topics.

Applied Optimization with MATLAB Programming

Author : P. Venkataraman
Publisher : John Wiley & Sons
ISBN 13 : 047008488X
Total Pages : 546 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Applied Optimization with MATLAB Programming by : P. Venkataraman

Download or read book Applied Optimization with MATLAB Programming written by P. Venkataraman and published by John Wiley & Sons. This book was released on 2009-03-23 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.

Bayesian Optimization with Application to Computer Experiments

Author : Tony Pourmohamad
Publisher : Springer Nature
ISBN 13 : 3030824586
Total Pages : 113 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Bayesian Optimization with Application to Computer Experiments by : Tony Pourmohamad

Download or read book Bayesian Optimization with Application to Computer Experiments written by Tony Pourmohamad and published by Springer Nature. This book was released on 2021-10-04 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to Bayesian optimization, highlighting advances in the field and showcasing its successful applications to computer experiments. R code is available as online supplementary material for most included examples, so that readers can better comprehend and reproduce methods. Compact and accessible, the volume is broken down into four chapters. Chapter 1 introduces the reader to the topic of computer experiments; it includes a variety of examples across many industries. Chapter 2 focuses on the task of surrogate model building and contains a mix of several different surrogate models that are used in the computer modeling and machine learning communities. Chapter 3 introduces the core concepts of Bayesian optimization and discusses unconstrained optimization. Chapter 4 moves on to constrained optimization, and showcases some of the most novel methods found in the field. This will be a useful companion to researchers and practitioners working with computer experiments and computer modeling. Additionally, readers with a background in machine learning but minimal background in computer experiments will find this book an interesting case study of the applicability of Bayesian optimization outside the realm of machine learning.