Heuristics For Optimization And Learning

Download Heuristics For Optimization And Learning full books in PDF, epub, and Kindle. Read online Heuristics For Optimization And Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Heuristics for Optimization and Learning

Author : Farouk Yalaoui
Publisher : Springer Nature
ISBN 13 : 3030589307
Total Pages : 444 pages
Book Rating : 4.0/5 (35 download)

DOWNLOAD NOW!

Book Synopsis Heuristics for Optimization and Learning by : Farouk Yalaoui

Download or read book Heuristics for Optimization and Learning written by Farouk Yalaoui and published by Springer Nature. This book was released on 2020-12-15 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Author : Vasant, Pandian M.
Publisher : IGI Global
ISBN 13 : 1466620870
Total Pages : 735 pages
Book Rating : 4.4/5 (666 download)

DOWNLOAD NOW!

Book Synopsis Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance by : Vasant, Pandian M.

Download or read book Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance written by Vasant, Pandian M. and published by IGI Global. This book was released on 2012-09-30 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Modern Heuristic Optimization Techniques

Author : Kwang Y. Lee
Publisher : John Wiley & Sons
ISBN 13 : 0470225858
Total Pages : 616 pages
Book Rating : 4.4/5 (72 download)

DOWNLOAD NOW!

Book Synopsis Modern Heuristic Optimization Techniques by : Kwang Y. Lee

Download or read book Modern Heuristic Optimization Techniques written by Kwang Y. Lee and published by John Wiley & Sons. This book was released on 2008-01-28 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores how developing solutions with heuristic tools offers two major advantages: shortened development time and more robust systems. It begins with an overview of modern heuristic techniques and goes on to cover specific applications of heuristic approaches to power system problems, such as security assessment, optimal power flow, power system scheduling and operational planning, power generation expansion planning, reactive power planning, transmission and distribution planning, network reconfiguration, power system control, and hybrid systems of heuristic methods.

Bioinspired Heuristics for Optimization

Author : El-Ghazali Talbi
Publisher : Springer
ISBN 13 : 3319951041
Total Pages : 314 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Bioinspired Heuristics for Optimization by : El-Ghazali Talbi

Download or read book Bioinspired Heuristics for Optimization written by El-Ghazali Talbi and published by Springer. This book was released on 2018-08-18 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some properties of intrinsic parallelization, and can be used for various optimizations problems. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software. It is a valuable resource for research academics and industrial practitioners.

Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics

Author : Thomas Stützle
Publisher : Springer Science & Business Media
ISBN 13 : 3642111688
Total Pages : 284 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

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.).

Metaheuristics and Nature Inspired Computing

Author : Bernabé Dorronsoro
Publisher : Springer Nature
ISBN 13 : 3030942163
Total Pages : 230 pages
Book Rating : 4.0/5 (39 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics and Nature Inspired Computing by : Bernabé Dorronsoro

Download or read book Metaheuristics and Nature Inspired Computing written by Bernabé Dorronsoro and published by Springer Nature. This book was released on 2022-02-21 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes selected papers presented during the 8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021, held in Marrakech, Morocco, in October 201. Due to the COVID-19 pandemic the conference was partiqally held online. The 16 papers were thoroughly reviewed and selected from the 53 submissions. They are organized in the topical sections on combinatorial optimization; continuous optimization; optimization and machine learning; applications.

Reactive Search and Intelligent Optimization

Author : Roberto Battiti
Publisher : Springer Science & Business Media
ISBN 13 : 0387096248
Total Pages : 198 pages
Book Rating : 4.3/5 (87 download)

DOWNLOAD NOW!

Book Synopsis Reactive Search and Intelligent Optimization by : Roberto Battiti

Download or read book Reactive Search and Intelligent Optimization written by Roberto Battiti and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics. Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities for the automated tuning of these parameters.

Meta-heuristic Optimization Techniques

Author : Anuj Kumar
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110716216
Total Pages : 202 pages
Book Rating : 4.1/5 (17 download)

DOWNLOAD NOW!

Book Synopsis Meta-heuristic Optimization Techniques by : Anuj Kumar

Download or read book Meta-heuristic Optimization Techniques written by Anuj Kumar and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-01-19 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offer a thorough overview of the most popular and researched meta-heuristic optimization techniques and nature inspired algorithms. Their wide applicability makes them a hot research topic and an efficient tool for the solution of complex optimization problems in various field of sciences, engineering and in numerous industries.

Applications of Modern Heuristic Optimization Methods in Power and Energy Systems

Author : Kwang Y. Lee
Publisher : John Wiley & Sons
ISBN 13 : 1119602297
Total Pages : 896 pages
Book Rating : 4.1/5 (196 download)

DOWNLOAD NOW!

Book Synopsis Applications of Modern Heuristic Optimization Methods in Power and Energy Systems by : Kwang Y. Lee

Download or read book Applications of Modern Heuristic Optimization Methods in Power and Energy Systems written by Kwang Y. Lee and published by John Wiley & Sons. This book was released on 2020-04-14 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reviews state-of-the-art technologies in modern heuristic optimization techniques and presents case studies showing how they have been applied in complex power and energy systems problems Written by a team of international experts, this book describes the use of metaheuristic applications in the analysis and design of electric power systems. This includes a discussion of optimum energy and commitment of generation (nonrenewable & renewable) and load resources during day-to-day operations and control activities in regulated and competitive market structures, along with transmission and distribution systems. Applications of Modern Heuristic Optimization Methods in Power and Energy Systems begins with an introduction and overview of applications in power and energy systems before moving on to planning and operation, control, and distribution. Further chapters cover the integration of renewable energy and the smart grid and electricity markets. The book finishes with final conclusions drawn by the editors. Applications of Modern Heuristic Optimization Methods in Power and Energy Systems: Explains the application of differential evolution in electric power systems' active power multi-objective optimal dispatch Includes studies of optimization and stability in load frequency control in modern power systems Describes optimal compliance of reactive power requirements in near-shore wind power plants Features contributions from noted experts in the field Ideal for power and energy systems designers, planners, operators, and consultants, Applications of Modern Heuristic Optimization Methods in Power and Energy Systems will also benefit engineers, software developers, researchers, academics, and students.

Heuristic and Optimization for Knowledge Discovery

Author : Abbass, Hussein A.
Publisher : IGI Global
ISBN 13 : 1591400171
Total Pages : 296 pages
Book Rating : 4.5/5 (914 download)

DOWNLOAD NOW!

Book Synopsis Heuristic and Optimization for Knowledge Discovery by : Abbass, Hussein A.

Download or read book Heuristic and Optimization for Knowledge Discovery written by Abbass, Hussein A. and published by IGI Global. This book was released on 2001-07-01 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the large amount of data stored by many organizations, capitalists have observed that this information is an intangible asset. Unfortunately, handling large databases is a very complex process and traditional learning techniques are expensive to use. Heuristic techniques provide much help in this arena, although little is known about heuristic techniques. Heuristic and Optimization for Knowledge Discovery addresses the foundation of this topic, as well as its practical uses, and aims to fill in the gap that exists in current literature.

Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems

Author : Essam Halim Houssein
Publisher : Springer Nature
ISBN 13 : 3030990796
Total Pages : 501 pages
Book Rating : 4.0/5 (39 download)

DOWNLOAD NOW!

Book Synopsis Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems by : Essam Halim Houssein

Download or read book Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems written by Essam Halim Houssein and published by Springer Nature. This book was released on 2022-06-04 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.

Metaheuristics

Author : Mauricio G.C. Resende
Publisher : Springer Science & Business Media
ISBN 13 : 9781402076534
Total Pages : 744 pages
Book Rating : 4.0/5 (765 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics by : Mauricio G.C. Resende

Download or read book Metaheuristics written by Mauricio G.C. Resende and published by Springer Science & Business Media. This book was released on 2003-11-30 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial optimization is the process of finding the best, or optimal, so lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo cation, logic, and assignment of resources. The economic impact of combi natorial optimization is profound, affecting sectors as diverse as transporta tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.

Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

Author : Omid Bozorg-Haddad
Publisher : John Wiley & Sons
ISBN 13 : 1119386993
Total Pages : 306 pages
Book Rating : 4.1/5 (193 download)

DOWNLOAD NOW!

Book Synopsis Meta-heuristic and Evolutionary Algorithms for Engineering Optimization by : Omid Bozorg-Haddad

Download or read book Meta-heuristic and Evolutionary Algorithms for Engineering Optimization written by Omid Bozorg-Haddad and published by John Wiley & Sons. This book was released on 2017-10-09 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

Metaheuristics

Author : El-Ghazali Talbi
Publisher : John Wiley & Sons
ISBN 13 : 0470496908
Total Pages : 625 pages
Book Rating : 4.4/5 (74 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics by : El-Ghazali Talbi

Download or read book Metaheuristics written by El-Ghazali Talbi and published by John Wiley & Sons. This book was released on 2009-05-27 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

Metaheuristics in Machine Learning: Theory and Applications

Author : Diego Oliva
Publisher : Springer Nature
ISBN 13 : 3030705420
Total Pages : 765 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristics in Machine Learning: Theory and Applications by : Diego Oliva

Download or read book Metaheuristics in Machine Learning: Theory and Applications written by Diego Oliva and published by Springer Nature. This book was released on with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Metaheuristic and Machine Learning Optimization Strategies for Complex Systems

Author : R., Thanigaivelan
Publisher : IGI Global
ISBN 13 :
Total Pages : 423 pages
Book Rating : 4.3/5 (693 download)

DOWNLOAD NOW!

Book Synopsis Metaheuristic and Machine Learning Optimization Strategies for Complex Systems by : R., Thanigaivelan

Download or read book Metaheuristic and Machine Learning Optimization Strategies for Complex Systems written by R., Thanigaivelan and published by IGI Global. This book was released on 2024-07-17 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more.

Learning Deep Architectures for AI

Author : Yoshua Bengio
Publisher : Now Publishers Inc
ISBN 13 : 1601982941
Total Pages : 145 pages
Book Rating : 4.6/5 (19 download)

DOWNLOAD NOW!

Book Synopsis Learning Deep Architectures for AI by : Yoshua Bengio

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.