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Meta Heuristics


Meta Heuristics
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Meta Heuristics


Meta Heuristics
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Author : Ibrahim H. Osman
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-03-31

Meta Heuristics written by Ibrahim H. Osman 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 1996-03-31 with Business & Economics categories.


Meta-heuristics have developed dramatically since their inception in the early 1980s. They have had widespread success in attacking a variety of practical and difficult combinatorial optimization problems. These families of approaches include, but are not limited to greedy random adaptive search procedures, genetic algorithms, problem-space search, neural networks, simulated annealing, tabu search, threshold algorithms, and their hybrids. They incorporate concepts based on biological evolution, intelligent problem solving, mathematical and physical sciences, nervous systems, and statistical mechanics. Since the 1980s, a great deal of effort has been invested in the field of combinatorial optimization theory in which heuristic algorithms have become an important area of research and applications. This volume is drawn from the first conference on Meta-Heuristics and contains 41 papers on the state-of-the-art in heuristic theory and applications. The book treats the following meta-heuristics and applications: Genetic Algorithms, Simulated Annealing, Tabu Search, Networks & Graphs, Scheduling and Control, TSP, and Vehicle Routing Problems. It represents research from the fields of Operations Research, Management Science, Artificial Intelligence and Computer Science.



Recent Advances On Meta Heuristics And Their Application To Real Scenarios


Recent Advances On Meta Heuristics And Their Application To Real Scenarios
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Author : Javier Del Ser Lorente
language : en
Publisher: BoD – Books on Demand
Release Date : 2013-01-30

Recent Advances On Meta Heuristics And Their Application To Real Scenarios written by Javier Del Ser Lorente and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-30 with Computers categories.


This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation. In summary, this book serves as a good start point for early-stage investigators in the initial steps of their research on meta-heuristics, grounded on both a thorough literature review and the practical orientation of its contents.



Metaheuristics


Metaheuristics
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Author : El-Ghazali Talbi
language : en
Publisher: John Wiley & Sons
Release Date : 2009-05-27

Metaheuristics written by El-Ghazali Talbi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-27 with Computers categories.


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.



Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems


Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems
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Author : Essam Halim Houssein
language : en
Publisher: Springer Nature
Release Date : 2022-06-04

Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems written by Essam Halim Houssein and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-04 with Technology & Engineering categories.


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.



Meta Heuristics


Meta Heuristics
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Author : Stefan Voß
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Meta Heuristics written by Stefan Voß 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 Business & Economics categories.


Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.



Meta Heuristics


Meta Heuristics
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Author : Ulrich Derigs
language : en
Publisher:
Release Date : 2004

Meta Heuristics written by Ulrich Derigs and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Combinatorial optimization categories.




Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance


Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance
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Author : Vasant, Pandian M.
language : en
Publisher: IGI Global
Release Date : 2012-09-30

Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance written by Vasant, Pandian M. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-30 with Computers categories.


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.



Optimization Algorithms In Machine Learning


Optimization Algorithms In Machine Learning
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Author : Debashish Das
language : en
Publisher: Springer Nature
Release Date : 2025-05-20

Optimization Algorithms In Machine Learning written by Debashish Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.


This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental learning, and grey wolf optimizer for training neural networks. Additionally, the book examines the challenges associated with these processes in detail. This volume will serve as a valuable reference for individuals in both academia and industry.



Recent Developments In Metaheuristics


Recent Developments In Metaheuristics
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Author : Lionel Amodeo
language : en
Publisher: Springer
Release Date : 2017-09-18

Recent Developments In Metaheuristics written by Lionel Amodeo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Business & Economics categories.


This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.



Meta Heuristic Optimization Techniques


Meta Heuristic Optimization Techniques
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Author : Anuj Kumar
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-01-19

Meta Heuristic Optimization Techniques written by Anuj Kumar and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-19 with Computers categories.


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.