Computing Tools for Modeling, Optimization and Simulation PDF Download

Author: Manuel Laguna
Publisher: Springer Science & Business Media
ISBN: 9780792377184
Category : Business & Economics
Languages : en
Pages : 330

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Book Description
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.

Author: Stefan Voß
Publisher: Springer Science & Business Media
ISBN: 3540247645
Category : Business & Economics
Languages : en
Pages : 239

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Book Description
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.

Author: Daniel Ashlock
Publisher: Springer Science & Business Media
ISBN: 0387319093
Category : Computers
Languages : en
Pages : 578

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Book Description
Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Author: Ciro D'Apice
Publisher: SIAM
ISBN: 0898717000
Category : Mathematics
Languages : en
Pages : 209

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Book Description
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.

Author: Winfried Keiper
Publisher: Springer
ISBN: 3319753193
Category : Mathematics
Languages : en
Pages : 184

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Book Description
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.

Author: S. K. Neogy
Publisher: World Scientific
ISBN: 9814273511
Category : Mathematics
Languages : en
Pages : 348

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Book Description
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.

Author: Slawomir Koziel
Publisher: Springer
ISBN: 3642208592
Category : Technology & Engineering
Languages : en
Pages : 292

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Book Description
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.

Author: Chun-hung Chen
Publisher: World Scientific
ISBN: 9814282642
Category : Computers
Languages : en
Pages : 246

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Book Description
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.

Author: Martin Pelikan
Publisher: Springer Science & Business Media
ISBN: 3540349537
Category : Mathematics
Languages : en
Pages : 363

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Book Description
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.

Author: Srikanta Patnaik
Publisher: Springer
ISBN: 3319509209
Category : Technology & Engineering
Languages : en
Pages : 506

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Book Description
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.