Share

Metaheuristics

2009-05-27 Computers
Download Metaheuristics PDF Online Free

Author :
Release : 2009-05-27
Genre : Computers
Kind : eBook
Book Rating : 908/5 ( reviews)

GET EBOOK


Book Synopsis Metaheuristics by : El-Ghazali Talbi

Download or read book Metaheuristics written by El-Ghazali Talbi. This book was released on 2009-05-27. 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.

Nature-inspired Metaheuristic Algorithms

2010 Computers
Download Nature-inspired Metaheuristic Algorithms PDF Online Free

Author :
Release : 2010
Genre : Computers
Kind : eBook
Book Rating : 289/5 ( reviews)

GET EBOOK


Book Synopsis Nature-inspired Metaheuristic Algorithms by : Xin-She Yang

Download or read book Nature-inspired Metaheuristic Algorithms written by Xin-She Yang. This book was released on 2010. Available in PDF, EPUB and Kindle. Book excerpt: Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Essentials of Metaheuristics (Second Edition)

2012-12-20 Algorithms
Download Essentials of Metaheuristics (Second Edition) PDF Online Free

Author :
Release : 2012-12-20
Genre : Algorithms
Kind : eBook
Book Rating : 628/5 ( reviews)

GET EBOOK


Book Synopsis Essentials of Metaheuristics (Second Edition) by : Sean Luke

Download or read book Essentials of Metaheuristics (Second Edition) written by Sean Luke. This book was released on 2012-12-20. Available in PDF, EPUB and Kindle. Book excerpt: Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA, BOA, SAMUEL, ZCS, XCS, and XCSF.

Handbook of Metaheuristics

2018-09-20 Business & Economics
Download Handbook of Metaheuristics PDF Online Free

Author :
Release : 2018-09-20
Genre : Business & Economics
Kind : eBook
Book Rating : 868/5 ( reviews)

GET EBOOK


Book Synopsis Handbook of Metaheuristics by : Michel Gendreau

Download or read book Handbook of Metaheuristics written by Michel Gendreau. This book was released on 2018-09-20. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

2020-11-13 Technology & Engineering
Download Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications PDF Online Free

Author :
Release : 2020-11-13
Genre : Technology & Engineering
Kind : eBook
Book Rating : 116/5 ( reviews)

GET EBOOK


Book Synopsis Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by : Modestus O. Okwu

Download or read book Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications written by Modestus O. Okwu. This book was released on 2020-11-13. Available in PDF, EPUB and Kindle. Book excerpt: This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

You may also like...