Adaptive Computer Algorithms For Optimization And Root Finding
DOWNLOAD
Download Adaptive Computer Algorithms For Optimization And Root Finding PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Adaptive Computer Algorithms For Optimization And Root Finding book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Adaptive Computer Algorithms For Optimization And Root Finding
DOWNLOAD
Author : Erich Schmitt
language : en
Publisher:
Release Date : 1969
Adaptive Computer Algorithms For Optimization And Root Finding written by Erich Schmitt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1969 with Algorithms categories.
Optimization By Grasp
DOWNLOAD
Author : Mauricio G.C. Resende
language : en
Publisher: Springer
Release Date : 2016-10-26
Optimization By Grasp written by Mauricio G.C. Resende and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-26 with Mathematics categories.
This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristic that has enjoyed wide success in practice with a broad range of applications to real-world combinatorial optimization problems. The state-of-the-art coverage and carefully crafted pedagogical style lends this book highly accessible as an introductory text not only to GRASP, but also to combinatorial optimization, greedy algorithms, local search, and path-relinking, as well as to heuristics and metaheuristics, in general. The focus is on algorithmic and computational aspects of applied optimization with GRASP with emphasis given to the end-user, providing sufficient information on the broad spectrum of advances in applied optimization with GRASP. For the more advanced reader, chapters on hybridization with path-relinking and parallel and continuous GRASP present these topics in a clear and concise fashion. Additionally, the book offers a very complete annotated bibliography of GRASP and combinatorial optimization. For the practitioner who needs to solve combinatorial optimization problems, the book provides a chapter with four case studies and implementable templates for all algorithms covered in the text. This book, with its excellent overview of GRASP, will appeal to researchers and practitioners of combinatorial optimization who have a need to find optimal or near optimal solutions to hard combinatorial optimization problems.
An Adaptive Random Search Algorithm For Implementation Of The Maximum Principle
DOWNLOAD
Author : Elwood C. Stewart
language : en
Publisher:
Release Date : 1970
An Adaptive Random Search Algorithm For Implementation Of The Maximum Principle written by Elwood C. Stewart and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Differential equations, Nonlinear categories.
Metaheuristic Optimization Via Memory And Evolution
DOWNLOAD
Author : Cesar Rego
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30
Metaheuristic Optimization Via Memory And Evolution written by Cesar Rego and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-30 with Business & Economics categories.
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
Adaptive And Natural Computing Algorithms
DOWNLOAD
Author : Bernadete Ribeiro
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-12
Adaptive And Natural Computing Algorithms written by Bernadete Ribeiro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-12 with Computers categories.
The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area. Starting in Innsbruck, in Austria (1993), then to Ales in Prance (1995), Norwich in England (1997), Portoroz in Slovenia (1999), Prague in the Czech Republic (2001) and finally Roanne, in France (2003), the ICANNGA series has established itself for experienced workers in the field. The series has also been of value to young researchers wishing both to extend their knowledge and experience and also to meet internationally renowned experts. The 2005 Conference, the seventh in the ICANNGA series, will take place at the University of Coimbra in Portugal, drawing on the experience of previous events, and following the same general model, combining technical sessions, including plenary lectures by renowned scientists, with tutorials.
Various Algorithms For Optimization And Learning In Adaptive Systems
DOWNLOAD
Author : Brooke P. Anderson
language : en
Publisher:
Release Date : 1993
Various Algorithms For Optimization And Learning In Adaptive Systems written by Brooke P. Anderson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
Multimodal Optimization By Means Of Evolutionary Algorithms
DOWNLOAD
Author : Mike Preuss
language : en
Publisher: Springer
Release Date : 2015-11-27
Multimodal Optimization By Means Of Evolutionary Algorithms written by Mike Preuss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-27 with Computers categories.
This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.
Scatter Search
DOWNLOAD
Author : Manuel Laguna
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Scatter Search written by Manuel Laguna and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
The book Scatter Search by Manuel Laguna and Rafael Martí represents a long-awaited "missing link" in the literature of evolutionary methods. Scatter Search (SS)-together with its generalized form called Path Relinking-constitutes the only evolutionary approach that embraces a collection of principles from Tabu Search (TS), an approach popularly regarded to be divorced from evolutionary procedures. The TS perspective, which is responsible for introducing adaptive memory strategies into the metaheuristic literature (at purposeful level beyond simple inheritance mechanisms), may at first seem to be at odds with population-based approaches. Yet this perspective equips SS with a remarkably effective foundation for solving a wide range of practical problems. The successes documented by Scatter Search come not so much from the adoption of adaptive memory in the range of ways proposed in Tabu Search (except where, as often happens, SS is advantageously coupled with TS), but from the use of strategic ideas initially proposed for exploiting adaptive memory, which blend harmoniously with the structure of Scatter Search. From a historical perspective, the dedicated use of heuristic strategies both to guide the process of combining solutions and to enhance the quality of offspring has been heralded as a key innovation in evolutionary methods, giving rise to what are sometimes called "hybrid" (or "memetic") evolutionary procedures. The underlying processes have been introduced into the mainstream of evolutionary methods (such as genetic algorithms, for example) by a series of gradual steps beginning in the late 1980s.
Search And Optimization By Metaheuristics
DOWNLOAD
Author : Ke-Lin Du
language : en
Publisher: Birkhäuser
Release Date : 2016-07-20
Search And Optimization By Metaheuristics written by Ke-Lin Du and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-20 with Computers categories.
This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.
Adaptive And Natural Computing Algorithms
DOWNLOAD
Author : Andrej Dobnikar
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-03
Adaptive And Natural Computing Algorithms written by Andrej Dobnikar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-03 with Computers categories.
The two-volume set LNCS 6593 and 6594 constitutes the refereed proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The 83 revised full papers presented were carefully reviewed and selected from a total of 144 submissions. The first volume includes 42 papers and a plenary lecture and is organized in topical sections on neural networks and evolutionary computation.