Computational Optimization, Methods and Algorithms

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Publisher : Springer
ISBN 13 : 3642208592
Total Pages : 292 pages
Book Rating : 4.91/5 ( 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.

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 : 4.47/5 ( 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.

Computational Optimization of Internal Combustion Engines

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Publisher : Springer Science & Business Media
ISBN 13 : 0857296191
Total Pages : 323 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Computational Optimization of Internal Combustion Engines by : Yu Shi

Download or read book Computational Optimization of Internal Combustion Engines written by Yu Shi and published by Springer Science & Business Media. This book was released on 2011-06-22 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Optimization of Internal Combustion Engines presents the state of the art of computational models and optimization methods for internal combustion engine development using multi-dimensional computational fluid dynamics (CFD) tools and genetic algorithms. Strategies to reduce computational cost and mesh dependency are discussed, as well as regression analysis methods. Several case studies are presented in a section devoted to applications, including assessments of: spark-ignition engines, dual-fuel engines, heavy duty and light duty diesel engines. Through regression analysis, optimization results are used to explain complex interactions between engine design parameters, such as nozzle design, injection timing, swirl, exhaust gas recirculation, bore size, and piston bowl shape. Computational Optimization of Internal Combustion Engines demonstrates that the current multi-dimensional CFD tools are mature enough for practical development of internal combustion engines. It is written for researchers and designers in mechanical engineering and the automotive industry.

Computational Optimization, Methods and Algorithms

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3642208584
Total Pages : 292 pages
Book Rating : 4.84/5 ( 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 Science & Business Media. 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.

Computational Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 1461551978
Total Pages : 266 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Computational Optimization by : Jong-Shi Pang

Download or read book Computational Optimization written by Jong-Shi Pang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Optimization: A Tribute to Olvi Mangasarian serves as an excellent reference, providing insight into some of the most challenging research issues in the field. This collection of papers covers a wide spectrum of computational optimization topics, representing a blend of familiar nonlinear programming topics and such novel paradigms as semidefinite programming and complementarity-constrained nonlinear programs. Many new results are presented in these papers which are bound to inspire further research and generate new avenues for applications. An informal categorization of the papers includes: Algorithmic advances for special classes of constrained optimization problems Analysis of linear and nonlinear programs Algorithmic advances B- stationary points of mathematical programs with equilibrium constraints Applications of optimization Some mathematical topics Systems of nonlinear equations.

Handbook of Machine Learning for Computational Optimization

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Publisher : CRC Press
ISBN 13 : 100045567X
Total Pages : 295 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Handbook of Machine Learning for Computational Optimization by : Vishal Jain

Download or read book Handbook of Machine Learning for Computational Optimization written by Vishal Jain and published by CRC Press. This book was released on 2021-11-02 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on new machine learning developments that can lead to newly developed applications Uses a predictive and futuristic approach which makes Machine Learning a promising tool for business processes and sustainable solutions Promotes newer algorithms which are more efficient and reliable for a new dimension in discovering certain latent domains of applications Discusses the huge potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making Offers many real-time case studies

Computational Optimization in Engineering

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Publisher : BoD – Books on Demand
ISBN 13 : 9535130811
Total Pages : 164 pages
Book Rating : 4.19/5 ( download)

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Book Synopsis Computational Optimization in Engineering by : Hossein Peyvandi

Download or read book Computational Optimization in Engineering written by Hossein Peyvandi and published by BoD – Books on Demand. This book was released on 2017-04-26 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of optimization is to maximize the quality of lives, productivity in time, as well as interests. Therefore, optimization is an ongoing challenge for selecting the best possible among many other inferior designs. For a hundred years in the past, as optimization has been essential to human life, several techniques have been developed and utilized. Such a development has been one of the long-lasting challenges in engineering and science, and it is now clear that the optimization goals in many of real-life problems are unlikely to be achieved without resource for computational techniques. The history of such a development in the optimization techniques starts from the early 1950s and is still in progress. Since then, the efforts behind this development dedicated by many distinguished scientists, mathematicians, and engineers have brought us today a level of quality of lives. This book concerns with the computational optimization in engineering and techniques to resolve the underlying problems in real life. The current book contains studies from scientists and researchers around the world from North America to Europe and from Asia to Australia.

Computational Combinatorial Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 3540428771
Total Pages : 317 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Computational Combinatorial Optimization by : Michael Jünger

Download or read book Computational Combinatorial Optimization written by Michael Jünger and published by Springer Science & Business Media. This book was released on 2001-11-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.

Evolutionary Computation for Modeling and Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 0387319093
Total Pages : 578 pages
Book Rating : 4.94/5 ( 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.

Bioinspired Computation in Combinatorial Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 3642165443
Total Pages : 215 pages
Book Rating : 4.43/5 ( download)

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Book Synopsis Bioinspired Computation in Combinatorial Optimization by : Frank Neumann

Download or read book Bioinspired Computation in Combinatorial Optimization written by Frank Neumann and published by Springer Science & Business Media. This book was released on 2010-11-04 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.