Simulation Based Optimization
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Natural Computing For Simulation Based Optimization And Beyond
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Author : Silja Meyer-Nieberg
language : en
Publisher: Springer
Release Date : 2019-07-26
Natural Computing For Simulation Based Optimization And Beyond written by Silja Meyer-Nieberg and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Business & Economics categories.
This SpringerBrief bridges the gap between the areas of simulation studies on the one hand, and optimization with natural computing on the other. Since natural computing methods have been applied with great success in several application areas, a review concerning potential benefits and pitfalls for simulation studies is merited. The brief presents such an overview and combines it with an introduction to natural computing and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review which covers both the methodological background and recent application cases. The brief is intended to serve two purposes: First, it can be used to gain more information concerning natural computing, its major dialects, and their usage for simulation studies. It also covers the areas of multi-objective optimization and neuroevolution. While the latter is only seldom mentioned in connection withsimulation studies, it is a powerful potential technique. Second, the reader is provided with an overview of several areas of simulation-based optimization which range from logistic problems to engineering tasks. Additionally, the brief focuses on the usage of surrogate and meta-models. The brief presents recent application examples.
Simulation Based Optimization
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Author : Abhijit Gosavi
language : en
Publisher: Springer
Release Date : 2014-10-30
Simulation Based Optimization written by Abhijit Gosavi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-30 with Business & Economics categories.
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.
High Performance Simulation Based Optimization
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Author : Thomas Bartz-Beielstein
language : en
Publisher: Springer
Release Date : 2019-06-01
High Performance Simulation Based Optimization written by Thomas Bartz-Beielstein and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-01 with Computers categories.
This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.
Simulation Based Lean Six Sigma And Design For Six Sigma
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Author : Basem El-Haik
language : en
Publisher: John Wiley & Sons
Release Date : 2006-10-27
Simulation Based Lean Six Sigma And Design For Six Sigma written by Basem El-Haik and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-27 with Technology & Engineering categories.
This is the first book to completely cover the whole body of knowledge of Six Sigma and Design for Six Sigma with Simulation Methods as outlined by the American Society for Quality. Both simulation and contemporary Six Sigma methods are explained in detail with practical examples that help understanding of the key features of the design methods. The systems approach to designing products and services as well as problem solving is integrated into the methods discussed.
Simulation Based Optimization Via Cutting Planes
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Author : Wei Wu
language : en
Publisher:
Release Date : 2009
Simulation Based Optimization Via Cutting Planes written by Wei Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Evaluating Fast And Efficient Modeling Methods For Simulation Based Optimization
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Author : Simon Lidberg
language : en
Publisher:
Release Date : 2021
Evaluating Fast And Efficient Modeling Methods For Simulation Based Optimization written by Simon Lidberg and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Simulation Based Optimization Approaches For Inventory Control
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Author : Guo Fei
language : en
Publisher:
Release Date : 2002
Simulation Based Optimization Approaches For Inventory Control written by Guo Fei and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Applied Simulation And Optimization
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Author : Miguel Mujica Mota
language : en
Publisher: Springer
Release Date : 2015-04-06
Applied Simulation And Optimization written by Miguel Mujica Mota and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-06 with Computers categories.
Presenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulation’s flexibility with optimization techniques’ robustness. Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.
Simulation Based Optimization Of Energy Efficiency In Production
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Author : Anna Carina Römer
language : en
Publisher: Springer Nature
Release Date : 2021-02-11
Simulation Based Optimization Of Energy Efficiency In Production written by Anna Carina Römer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-11 with Business & Economics categories.
The importance of the energy and commodity markets has steadily increased since the first oil crisis. The sustained use of energy and other resources has become a basic requirement for a company to competitively perform on the market. The modeling, analysis and assessment of dynamic production processes is often performed using simulation software. While existing approaches mainly focus on the consideration of resource consumption variables based on metrologically collected data on operating states, the aim of this work is to depict the energy consumption of production plants through the utilization of a continuous simulation approach in combination with a discrete approach for the modeling of material flows and supporting logistic processes. The complex interactions between the material flow and the energy usage in production can thus be simulated closer to reality, especially the depiction of energy consumption peaks becomes possible. An essential step towards reducing energy consumption in production is the optimization of the energy use of non-value-adding production phases.
Uncertainty Management In Simulation Optimization Of Complex Systems
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Author : Gabriella Dellino
language : en
Publisher: Springer
Release Date : 2015-06-29
Uncertainty Management In Simulation Optimization Of Complex Systems written by Gabriella Dellino and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-29 with Business & Economics categories.
This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together — as chapter contributors — researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors’ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.