Computing Tools for Modeling, Optimization and Simulation

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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.

Evolutionary Computation for Modeling and Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 0387319093
Total Pages : 578 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Evolutionary Computation for Modeling and Optimization by : Daniel Ashlock

Download or read book Evolutionary Computation for Modeling and Optimization written by Daniel Ashlock and published by Springer Science & Business Media. This book was released on 2006-04-04 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Introduction to Computational Optimization Models for Production Planning in a Supply Chain

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Publisher : Springer Science & Business Media
ISBN 13 : 3540247645
Total Pages : 239 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Introduction to Computational Optimization Models for Production Planning in a Supply Chain by : Stefan Voß

Download or read book Introduction to Computational Optimization Models for Production Planning in a Supply Chain written by Stefan Voß and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy-to-read introduction to the concepts associated with the creation of optimization models for production planning starts off this book. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, fairly sophisticated models for supply chain management are developed. Another unique feature is that models are developed with an eye toward implementation. In fact, there is a chapter that provides explicit examples of implementation of the basic models using a variety of popular, commercially available modeling languages.

Reduced-Order Modeling (ROM) for Simulation and Optimization

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Publisher : Springer
ISBN 13 : 3319753193
Total Pages : 184 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Reduced-Order Modeling (ROM) for Simulation and Optimization by : Winfried Keiper

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 184 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.

Modeling, Simulation, and Optimization of Supply Chains

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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.

Modeling, Computation and Optimization

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Publisher : World Scientific
ISBN 13 : 9814273503
Total Pages : 348 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Modeling, Computation and Optimization by : S. K. Neogy

Download or read book Modeling, Computation and Optimization written by S. K. Neogy and published by World Scientific. This book was released on 2009 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides recent developments and a state-of-the-art review in various areas of mathematical modeling, computation and optimization. It contains theory, computation as well as the applications of several mathematical models to problems in statistics, games, optimization and economics for decision making. It focuses on exciting areas like models for wireless networks, models of Nash networks, dynamic models of advertising, application of reliability models in economics, support vector machines, optimization, complementarity modeling and games.

Computational Optimization, Methods and Algorithms

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Publisher : Springer
ISBN 13 : 3642208592
Total Pages : 292 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Computational Optimization, Methods and Algorithms by : Slawomir Koziel

Download or read book Computational Optimization, Methods and Algorithms written by Slawomir Koziel and published by Springer. This book was released on 2011-06-17 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Stochastic Simulation Optimization

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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.

Nature-Inspired Computing and Optimization

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Publisher : Springer
ISBN 13 : 3319509209
Total Pages : 506 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Nature-Inspired Computing and Optimization by : Srikanta Patnaik

Download or read book Nature-Inspired Computing and Optimization written by Srikanta Patnaik and published by Springer. This book was released on 2017-03-07 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

Scalable Optimization via Probabilistic Modeling

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Publisher : Springer Science & Business Media
ISBN 13 : 3540349537
Total Pages : 363 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Scalable Optimization via Probabilistic Modeling by : Martin Pelikan

Download or read book Scalable Optimization via Probabilistic Modeling written by Martin Pelikan and published by Springer Science & Business Media. This book was released on 2006-09-25 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.

Modeling, Simulation, and Optimization

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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.

Modelling, Computation and Optimization in Information Systems and Management Sciences

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Publisher : Springer
ISBN 13 : 9783030926656
Total Pages : 404 pages
Book Rating : 4.9/5 (266 download)

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Book Synopsis Modelling, Computation and Optimization in Information Systems and Management Sciences by : Hoai An Le Thi

Download or read book Modelling, Computation and Optimization in Information Systems and Management Sciences written by Hoai An Le Thi and published by Springer. This book was released on 2021-12-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings consist of 34 papers which have been submitted to the 4th international conference on Modelling, Computation & Optimization in Information Systems and Management Science (MCO 2021) held on 11-13 December, 2021 at Hanoi, Vietnam. The book is composed of 3 parts: Optimization of complex systems - models and methods, Machine Learning - algorithms and applications, and Cryptography. All chapters in the books discuss theoretical and algorithmic as well as practical issues connected with modelling, computation & optimization in Information Systems and Management Science. Researchers and practitioners in related areas will find a wealth of inspiring ideas and useful tools & techniques for their own work.

Simulation-Based Optimization

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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.

Advances in Mathematical Modeling, Optimization and Optimal Control

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Publisher : Springer
ISBN 13 : 3319307851
Total Pages : 205 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Advances in Mathematical Modeling, Optimization and Optimal Control by : Jean-Baptiste Hiriart-Urruty

Download or read book Advances in Mathematical Modeling, Optimization and Optimal Control written by Jean-Baptiste Hiriart-Urruty and published by Springer. This book was released on 2016-05-19 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains extended, in-depth presentations of the plenary talks from the 16th French-German-Polish Conference on Optimization, held in Kraków, Poland in 2013. Each chapter in this book exhibits a comprehensive look at new theoretical and/or application-oriented results in mathematical modeling, optimization, and optimal control. Students and researchers involved in image processing, partial differential inclusions, shape optimization, or optimal control theory and its applications to medical and rehabilitation technology, will find this book valuable. The first chapter by Martin Burger provides an overview of recent developments related to Bregman distances, which is an important tool in inverse problems and image processing. The chapter by Piotr Kalita studies the operator version of a first order in time partial differential inclusion and its time discretization. In the chapter by Günter Leugering, Jan Sokołowski and Antoni Żochowski, nonsmooth shape optimization problems for variational inequalities are considered. The next chapter, by Katja Mombaur is devoted to applications of optimal control and inverse optimal control in the field of medical and rehabilitation technology, in particular in human movement analysis, therapy and improvement by means of medical devices. The final chapter, by Nikolai Osmolovskii and Helmut Maurer provides a survey on no-gap second order optimality conditions in the calculus of variations and optimal control, and a discussion of their further development.

Optimization Models

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Publisher : Cambridge University Press
ISBN 13 : 1107050871
Total Pages : 651 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Optimization Models by : Giuseppe C. Calafiore

Download or read book Optimization Models written by Giuseppe C. Calafiore and published by Cambridge University Press. This book was released on 2014-10-31 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.

Modeling Languages in Mathematical Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 1461302153
Total Pages : 427 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Modeling Languages in Mathematical Optimization by : Josef Kallrath

Download or read book Modeling Languages in Mathematical Optimization written by Josef Kallrath and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a unique combination of modeling and solving real world optimization problems. It is the only book which treats systematically the major modeling languages and systems used to solve mathematical optimization problems, and it also provides a useful overview and orientation of today's modeling languages in mathematical optimization. It demonstrates the strengths and characteristic features of such languages and provides a bridge for researchers, practitioners and students into a new world: solving real optimization problems with the most advances modeling systems.

Linear Network Optimization

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Publisher : MIT Press
ISBN 13 : 9780262023344
Total Pages : 384 pages
Book Rating : 4.0/5 (233 download)

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Book Synopsis Linear Network Optimization by : Dimitri P. Bertsekas

Download or read book Linear Network Optimization written by Dimitri P. Bertsekas and published by MIT Press. This book was released on 1991 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems.