Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics
Download Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics full books in PDF, epub, and Kindle. Read online Engineering Stochastic Local Search Algorithms Designing Implementing And Analyzing Effective Heuristics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics by : Thomas Stützle
Download or read book Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics written by Thomas Stützle and published by Springer. This book was released on 2007-08-22 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms. Inside the volume, readers will find twelve full papers as well as nine short papers. Topics include methodological developments, behavior of SLS algorithms, search space analysis, algorithm performance, tuning procedures, AI/OR techniques, and dynamic behavior.
Book Synopsis Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics by : Thomas Stützle
Download or read book Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics written by Thomas Stützle and published by Springer. This book was released on 2009-09-01 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics.
Book Synopsis Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics by : Thomas Stützle
Download or read book Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics written by Thomas Stützle and published by Springer. This book was released on 2007-08-28 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms. Inside the volume, readers will find twelve full papers as well as nine short papers. Topics include methodological developments, behavior of SLS algorithms, search space analysis, algorithm performance, tuning procedures, AI/OR techniques, and dynamic behavior.
Book Synopsis Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics by : Thomas Stützle
Download or read book Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics written by Thomas Stützle and published by Springer Science & Business Media. This book was released on 2009-12-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Learning and Intelligent Optimization, LION 2009 III, held in Trento, Italy, in January 2009. The 15 revised full papers, one extended abstract and two poster sessions were carefully reviewed and selected from 86 submissions for inclusion in the book. The papers cover current issues of stochastic local search methods and meta-heuristics, hybridizations of constraint and mathematical programming with meta-heuristics, supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search (online self-tuning methods), algorithm portfolios and off-line tuning methods, algorithms for dynamic, stochastic and multi-objective problems, interface(s) between discrete and continuous optimization, experimental analysis and modeling of algorithms, theoretical foundations, parallelization of optimization algorithms, memory-based optimization, prohibition-based methods (tabu search), memetic algorithms, evolutionary algorithms, dynamic local search, iterated local search, variable neighborhood search and swarm intelligence methods (ant colony optimization, particle swarm optimization etc.).
Book Synopsis Stochastic Local Search by : Holger H. Hoos
Download or read book Stochastic Local Search written by Holger H. Hoos and published by Elsevier. This book was released on 2004-09-28 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. Provides the first unified view of the field Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms
Book Synopsis Stochastic Local Search - Methods, Models, Applications by : Holger Hoos
Download or read book Stochastic Local Search - Methods, Models, Applications written by Holger Hoos and published by IOS Press. This book was released on 1999 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: To date, stochastic local search (SLS) algorithms are among the standard methods for solving hard combinatorial problems from various areas of Artificial Intelligence and Operations Research. Some of the most successful and powerful algorithms for prominent problems like SAT, CSP, or TSP are based on stochastic local search. This work investigates various aspects of SLS algorithms; in particular, it focusses on modelling these algorithms, empirically evaluating their performance, characterising and improving their behaviour, and understanding the factors which influence their efficiency. These issues are studied for the SAT problem in propositional logic as a primary application domain. SAT has the advantage of being conceptually very simple, which facilitates the design, implementation, and presentation of algorithms as well as their analysis. However, most of the methodology generalises easily to other combinatorial problems like CSP. This Ph.D. thesis won the Best Dissertation Award 1999 (Dissertationspreis) of the German Informatics Society (Gesellschaft fur Informatik).
Book Synopsis Recent Advances in Evolutionary Computation for Combinatorial Optimization by : Carlos Cotta
Download or read book Recent Advances in Evolutionary Computation for Combinatorial Optimization written by Carlos Cotta and published by Springer. This book was released on 2008-09-08 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems. The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective.
Book Synopsis Springer Handbook of Computational Intelligence by : Janusz Kacprzyk
Download or read book Springer Handbook of Computational Intelligence written by Janusz Kacprzyk and published by Springer. This book was released on 2015-05-28 with total page 1637 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Book Synopsis Encyclopedia of Business Analytics and Optimization by : Wang, John
Download or read book Encyclopedia of Business Analytics and Optimization written by Wang, John and published by IGI Global. This book was released on 2014-02-28 with total page 2862 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Book Synopsis Handbook of Approximation Algorithms and Metaheuristics by : Teofilo F. Gonzalez
Download or read book Handbook of Approximation Algorithms and Metaheuristics written by Teofilo F. Gonzalez and published by CRC Press. This book was released on 2018-05-15 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Book Synopsis Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods by : Minis, Ioannis
Download or read book Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods written by Minis, Ioannis and published by IGI Global. This book was released on 2010-12-31 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence (CI) is a term corresponding to a new generation of algorithmic methodologies in artificial intelligence, which combines elements of learning, adaptation, evolution and approximate (fuzzy) reasoning to create programs that can be considered intelligent. Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods presents computational intelligence methods for addressing supply chain issues. Emphasis is given to techniques that provide effective solutions to complex supply chain problems and exhibit superior performance to other methods of operations research.
Book Synopsis Optimization Methods in Logistics by : Kaveh Sheibani
Download or read book Optimization Methods in Logistics written by Kaveh Sheibani and published by ORLAB Analytics. This book was released on 2014-06-30 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations Research and Logistics are strongly connected: most of the theoretical developments of the former have been motivated by applications in the latter. The spirit of this special issue on Optimization Methods in Logistics moves along the same line, with methodological approaches presented to respond to the needs of practitioners. Applications emerging in different branches of the wide field of logistics have been addressed by authors from Belgium, Brazil, Singapore, Spain, Switzerland, Thailand and the USA.
Book Synopsis Machine Learning Assisted Evolutionary Multi- and Many-Objective Optimization by : Dhish Kumar Saxena
Download or read book Machine Learning Assisted Evolutionary Multi- and Many-Objective Optimization written by Dhish Kumar Saxena and published by Springer Nature. This book was released on with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithm Portfolios by : Dimitris Souravlias
Download or read book Algorithm Portfolios written by Dimitris Souravlias and published by Springer Nature. This book was released on 2021-03-24 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.
Book Synopsis Nature-Inspired Intelligent Computing Techniques in Bioinformatics by : Khalid Raza
Download or read book Nature-Inspired Intelligent Computing Techniques in Bioinformatics written by Khalid Raza and published by Springer Nature. This book was released on 2022-10-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book encapsulates and occupies recent advances and state-of-the-art applications of nature-inspired computing (NIC) techniques in the field of bioinformatics and computational biology, which would aid medical sciences in various clinical applications. This edited volume covers fundamental applications, scope, and future perspectives of NIC techniques in bioinformatics including genomic profiling, gene expression data classification, DNA computation, systems and network biology, solving personalized therapy complications, antimicrobial resistance in bacterial pathogens, and computer-aided drug design, discovery, and therapeutics. It also covers the role of NIC techniques in various diseases and disorders, including cancer detection and diagnosis, breast cancer, lung disorder detection, disease biomarkers, and potential therapeutics identifications.
Book Synopsis Computation and Big Data for Transport by : Pedro Diez
Download or read book Computation and Big Data for Transport written by Pedro Diez and published by Springer Nature. This book was released on 2020-02-28 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the outcomes of the second ECCOMAS CM3 Conference series on transport, which addressed the main challenges and opportunities that computation and big data represent for transport and mobility in the automotive, logistics, aeronautics and marine-maritime fields. Through a series of plenary lectures and mini-forums with lectures followed by question-and-answer sessions, the conference explored potential solutions and innovations to improve transport and mobility in surface and air applications. The book seeks to answer the question of how computational research in transport can provide innovative solutions to Green Transportation challenges identified in the ambitious Horizon 2020 program. In particular, the respective papers present the state of the art in transport modeling, simulation and optimization in the fields of maritime, aeronautics, automotive and logistics research. In addition, the content includes two white papers on transport challenges and prospects. Given its scope, the book will be of interest to students, researchers, engineers and practitioners whose work involves the implementation of Intelligent Transport Systems (ITS) software for the optimal use of roads, including safety and security, traffic and travel data, surface and air traffic management, and freight logistics.
Book Synopsis Combinations of Intelligent Methods and Applications by : Ioannis Hatzilygeroudis
Download or read book Combinations of Intelligent Methods and Applications written by Ioannis Hatzilygeroudis and published by Springer. This book was released on 2016-01-27 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014).
