Metaheuristic Optimization Algorithms

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Search and Optimization by Metaheuristics

Author : Ke-Lin Du
Publisher : Birkhäuser
ISBN 13 : 3319411926
Total Pages : 434 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Search and Optimization by Metaheuristics by : Ke-Lin Du

Download or read book Search and Optimization by Metaheuristics written by Ke-Lin Du and published by Birkhäuser. This book was released on 2016-07-20 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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

Author : Modestus O. Okwu
Publisher : Springer Nature
ISBN 13 : 3030611116
Total Pages : 192 pages
Book Rating : 4.0/5 (36 download)

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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 and published by Springer Nature. This book was released on 2020-11-13 with total page 192 pages. 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.

Nature-Inspired Methods for Metaheuristics Optimization

Author : Fouad Bennis
Publisher : Springer Nature
ISBN 13 : 3030264580
Total Pages : 503 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Nature-Inspired Methods for Metaheuristics Optimization by : Fouad Bennis

Download or read book Nature-Inspired Methods for Metaheuristics Optimization written by Fouad Bennis and published by Springer Nature. This book was released on 2020-01-17 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

Nature-inspired Metaheuristic Algorithms

Author : Xin-She Yang
Publisher : Luniver Press
ISBN 13 : 1905986289
Total Pages : 148 pages
Book Rating : 4.9/5 (59 download)

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

Download or read book Nature-inspired Metaheuristic Algorithms written by Xin-She Yang and published by Luniver Press. This book was released on 2010 with total page 148 pages. 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.

Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Author : A. Kaveh
Publisher : Springer
ISBN 13 : 331948012X
Total Pages : 373 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Applications of Metaheuristic Optimization Algorithms in Civil Engineering by : A. Kaveh

Download or read book Applications of Metaheuristic Optimization Algorithms in Civil Engineering written by A. Kaveh and published by Springer. This book was released on 2016-11-30 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.

Metaheuristic Optimization Algorithms in Civil Engineering: New Applications

Author : Ali Kaveh
Publisher : Springer Nature
ISBN 13 : 3030454738
Total Pages : 382 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Metaheuristic Optimization Algorithms in Civil Engineering: New Applications by : Ali Kaveh

Download or read book Metaheuristic Optimization Algorithms in Civil Engineering: New Applications written by Ali Kaveh and published by Springer Nature. This book was released on 2020-04-14 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the application of metaheuristic algorithms in a number of important optimization problems in civil engineering. Advances in civil engineering technologies require greater accuracy, efficiency and speed in terms of the analysis and design of the corresponding systems. As such, it is not surprising that novel methods have been developed for the optimal design of real-world systems and models with complex configurations and large numbers of elements. This book is intended for scientists, engineers and students wishing to explore the potential of newly developed metaheuristics in practical problems. It presents concepts that are not only applicable to civil engineering problems, but can also used for optimizing problems related to mechanical, electrical, and industrial engineering. It is an essential resource for civil, mechanical and electrical engineers who use optimization methods for design, as well as for students and researchers interested in structural optimization.

Engineering Optimization

Author : Xin-She Yang
Publisher : John Wiley & Sons
ISBN 13 : 0470640413
Total Pages : 377 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Engineering Optimization by : Xin-She Yang

Download or read book Engineering Optimization written by Xin-She Yang and published by John Wiley & Sons. This book was released on 2010-07-20 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences From engineering and computer science to economics and management science, optimization is a core component for problem solving. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An Introduction with Metaheuristic Applications outlines popular metaheuristic algorithms and equips readers with the skills needed to apply these techniques to their own optimization problems. With insightful examples from various fields of study, the author highlights key concepts and techniques for the successful application of commonly-used metaheuristc algorithms, including simulated annealing, particle swarm optimization, harmony search, and genetic algorithms. The author introduces all major metaheuristic algorithms and their applications in optimization through a presentation that is organized into three succinct parts: Foundations of Optimization and Algorithms provides a brief introduction to the underlying nature of optimization and the common approaches to optimization problems, random number generation, the Monte Carlo method, and the Markov chain Monte Carlo method Metaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle swarm optimization, firefly algorithms, and harmony search Applications outlines a wide range of applications that use metaheuristic algorithms to solve challenging optimization problems with detailed implementation while also introducing various modifications used for multi-objective optimization Throughout the book, the author presents worked-out examples and real-world applications that illustrate the modern relevance of the topic. A detailed appendix features important and popular algorithms using MATLAB® and Octave software packages, and a related FTP site houses MATLAB code and programs for easy implementation of the discussed techniques. In addition, references to the current literature enable readers to investigate individual algorithms and methods in greater detail. Engineering Optimization: An Introduction with Metaheuristic Applications is an excellent book for courses on optimization and computer simulation at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners working in the fields of mathematics, engineering, computer science, operations research, and management science who use metaheuristic algorithms to solve problems in their everyday work.

Optimization Using Evolutionary Algorithms and Metaheuristics

Author : Kaushik Kumar
Publisher : CRC Press
ISBN 13 : 1000546802
Total Pages : 138 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Optimization Using Evolutionary Algorithms and Metaheuristics by : Kaushik Kumar

Download or read book Optimization Using Evolutionary Algorithms and Metaheuristics written by Kaushik Kumar and published by CRC Press. This book was released on 2019-08-22 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering

An Introduction to Metaheuristics for Optimization

Author : Bastien Chopard
Publisher : Springer
ISBN 13 : 3319930737
Total Pages : 226 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis An Introduction to Metaheuristics for Optimization by : Bastien Chopard

Download or read book An Introduction to Metaheuristics for Optimization written by Bastien Chopard and published by Springer. This book was released on 2018-11-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

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)

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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.

A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

Author : Oscar Castillo
Publisher : Springer Nature
ISBN 13 : 3030822885
Total Pages : 76 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics by : Oscar Castillo

Download or read book A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics written by Oscar Castillo and published by Springer Nature. This book was released on 2021-08-18 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.

Essentials of Metaheuristics (Second Edition)

Author : Sean Luke
Publisher :
ISBN 13 : 9781300549628
Total Pages : 242 pages
Book Rating : 4.5/5 (496 download)

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

Download or read book Essentials of Metaheuristics (Second Edition) written by Sean Luke and published by . This book was released on 2012-12-20 with total page 242 pages. 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.

Meta-heuristic Optimization Techniques

Author : Anuj Kumar
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110716259
Total Pages : 219 pages
Book Rating : 4.1/5 (17 download)

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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 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers 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 effi cient tool for the solution of complex optimization problems in various fi elds of sciences, engineering, and in numerous industries.

Metaheuristics for Hard Optimization

Author : Johann Dréo
Publisher : Springer Science & Business Media
ISBN 13 : 3540309667
Total Pages : 373 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Metaheuristics for Hard Optimization by : Johann Dréo

Download or read book Metaheuristics for Hard Optimization written by Johann Dréo and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains case studies from engineering and operations research Includes commented literature for each chapter

Metaheuristics and Optimization in Computer and Electrical Engineering

Author : Navid Razmjooy
Publisher : Springer Nature
ISBN 13 : 3030566897
Total Pages : 311 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Metaheuristics and Optimization in Computer and Electrical Engineering by : Navid Razmjooy

Download or read book Metaheuristics and Optimization in Computer and Electrical Engineering written by Navid Razmjooy and published by Springer Nature. This book was released on 2020-11-16 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.

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)

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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.

Nature-Inspired Optimization Algorithms

Author : Xin-She Yang
Publisher : Elsevier
ISBN 13 : 0124167454
Total Pages : 277 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang

Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm