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.

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.

Download or read book Simulation and Optimization in Finance written by Dessislava A. Pachamanova and published by John Wiley & Sons. This book was released on 2010-09-23 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.

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.

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.

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 129 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.

Download or read book Simulation and Optimization in Process Engineering written by Michael Bortz and published by Elsevier. This book was released on 2022-04-16 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation and Optimization in Process Engineering: The Benefit of Mathematical Methods in Applications of the Process Industry brings together examples where the successful transfer of progress made in mathematical simulation and optimization has led to innovations in an industrial context that created substantial benefit. Containing introductory accounts on scientific progress in the most relevant topics of process engineering (substance properties, simulation, optimization, optimal control and real time optimization), the examples included illustrate how such scientific progress has been transferred to innovations that delivered a measurable impact, covering details of the methods used, and more. With each chapter bringing together expertise from academia and industry, this book is the first of its kind, providing demonstratable insights. Recent mathematical methods are transformed into industrially relevant innovations. Covers recent progress in mathematical simulation and optimization in a process engineering context with chapters written by experts from both academia and industry Provides insight into challenges in industry aiming for a digitized world.

Download or read book Stochastic Simulation Optimization For Discrete Event Systems Perturbation Analysis Ordinal Optimization And Beyond written by Chun-hung Chen and published by World Scientific. This book was released on 2013-07-03 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete event systems (DES) have become pervasive in our daily lives. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling these stochastic simulations has long been a “hard nut to crack”. The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y C Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions.

Download or read book Optimization of Stochastic Models written by Georg Ch. Pflug and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

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.

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.

Download or read book VLSI Circuit Simulation and Optimization written by V. Litovski and published by Springer Science & Business Media. This book was released on 1996-12-31 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Circuit simulation has become an essential tool in circuit design and without it's aid, analogue and mixed-signal IC design would be impossible. However the applicability and limitations of circuit simulators have not been generally well understood and this book now provides a clear and easy to follow explanation of their function. The material covered includes the algorithms used in circuit simulation and the numerical techniques needed for linear and non-linear DC analysis, transient analysis and AC analysis. The book goes on to explain the numeric methods to include sensitivity and tolerance analysis and optimisation of component values for circuit design. The final part deals with logic simulation and mixed-signal simulation algorithms. There are comprehensive and detailed descriptions of the numerical methods and the material is presented in a way that provides for the needs of both experienced engineers who wish to extend their knowledge of current tools and techniques, and of advanced students and researchers who wish to develop new simulators.

Download or read book Reduced Order Modeling ROM for Simulation and Optimization written by Winfried Keiper and published by Springer. This book was released on 2018-04-11 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike.

Download or read book Data Analysis Optimization and Simulation Modeling written by S. Christian Albright and published by . This book was released on 2011 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: DATA ANALYSIS, OPTIMIZATION, AND SIMULATION MODELING, 4e, International Edition is a teach-by-example approach, learner-friendly writing style, and complete Excel integration focusing on data analysis, modeling, and spreadsheet use in statistics and management science. The Premium Online Content Website (accessed by a unique code with every new book) includes links to the following add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); and SolverTable, allowing users to do sensitivity analysis. All of the add-ins is revised for Excel 2007 and notes about Excel 2010 are added where applicable.

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 2012-12-06 with total page 318 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.

Download or read book Design Simulation and Optimization of Adsorptive and Chromatographic Separations A Hands On Approach written by Kevin R. Wood and published by John Wiley & Sons. This book was released on 2018-07-16 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource to the construction, use, and modification of the wide variety of adsorptive and chromatographic separations Design, Simulation and Optimization of Adsorptive and Chromatographic Separations offers the information needed to effectively design, simulate, and optimize adsorptive and chromatographic separations for a wide range of industrial applications. The authors?noted experts in the field?cover the fundamental principles, the applications, and a range of modeling techniques for the processes. The text presents a unified approach that includes the ideal and intermediate equations and offers a wealth of hands-on case studies that employ the rigorous simulation packages Aspen Adsorption and Aspen Chromatography. The text reviews the effective design strategies, details design considerations, and the assumptions which the modelers are allowed to make. The authors also cover shortcut design methods as well as mathematical tools that help to determine optimal operating conditions. This important text: -Covers everything from the underlying pheonmena to model optimization and the customization of model code -Includes practical tutorials that allow for independent review and study -Offers a comprehensive review of the construction, use, and modification of the wide variety of adsorptive and chromatographic separations -Contains contributions from three noted experts in the field Written for chromatographers, process engineers, ehemists, and other professionals, Design, Simulation and Optimization of Adsorptive and Chromatographic Separations offers a comprehensive review of the construction, use, and modification of adsorptive and chromatographic separations.

Download or read book Mathematical Modeling Simulation and Optimization for Power Engineering and Management written by Simone Göttlich and published by Springer Nature. This book was released on 2021-02-02 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks. Over twenty authors focus on the mathematical modeling of such future systems with careful analysis of desired properties and arising scales. Numerical investigations include efficient methods for the simulation of possibly large-scale interconnected energy systems and modern techniques for optimization purposes to guarantee stable and reliable future operations. The target audience comprises research scientists, researchers in the R&D field, and practitioners. Since the book highlights possible future research directions, graduate students in the field of mathematical modeling or electrical engineering may also benefit strongly.