Optimization Using Evolutionary Algorithms And Metaheuristics

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Optimization Using Evolutionary Algorithms and Metaheuristics

Kaushik Kumar,J. Paulo Davim
Optimization Using Evolutionary Algorithms and Metaheuristics Book PDF

Author : Kaushik Kumar,J. Paulo Davim
Publisher : CRC Press
Page : 138 pages
File Size : 53,9 Mb
Release : 2019-08-22
Category : Technology & Engineering
ISBN : 9781000546804

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Optimization Using Evolutionary Algorithms and Metaheuristics by Kaushik Kumar,J. Paulo Davim Pdf

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

Optimization Using Evolutionary Algorithms and Metaheuristics

Kaushik Kumar,J. Paulo Davim
Optimization Using Evolutionary Algorithms and Metaheuristics Book PDF

Author : Kaushik Kumar,J. Paulo Davim
Publisher : CRC Press
Page : 136 pages
File Size : 42,5 Mb
Release : 2019-08-22
Category : Technology & Engineering
ISBN : 9781000537147

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Optimization Using Evolutionary Algorithms and Metaheuristics by Kaushik Kumar,J. Paulo Davim Pdf

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

Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga
Meta heuristic and Evolutionary Algorithms for Engineering Optimization Book PDF

Author : Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga
Publisher : John Wiley & Sons
Page : 306 pages
File Size : 44,5 Mb
Release : 2017-10-09
Category : Mathematics
ISBN : 9781119386995

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Meta-heuristic and Evolutionary Algorithms for Engineering Optimization by Omid Bozorg-Haddad,Mohammad Solgi,Hugo A. Loáiciga Pdf

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.

Search and Optimization by Metaheuristics

Ke-Lin Du,M. N. S. Swamy
Search and Optimization by Metaheuristics Book PDF

Author : Ke-Lin Du,M. N. S. Swamy
Publisher : Birkhäuser
Page : 434 pages
File Size : 53,7 Mb
Release : 2016-07-20
Category : Computers
ISBN : 9783319411927

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Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy Pdf

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.

Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms

André A. Keller
Multi Objective Optimization in Theory and Practice II Metaheuristic Algorithms Book PDF

Author : André A. Keller
Publisher : Bentham Science Publishers
Page : 310 pages
File Size : 41,5 Mb
Release : 2019-03-28
Category : Mathematics
ISBN : 9781681087061

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Multi-Objective Optimization in Theory and Practice II: Metaheuristic Algorithms by André A. Keller Pdf

Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.

Advances in Metaheuristics for Hard Optimization

Patrick Siarry,Zbigniew Michalewicz
Advances in Metaheuristics for Hard Optimization Book PDF

Author : Patrick Siarry,Zbigniew Michalewicz
Publisher : Springer Science & Business Media
Page : 481 pages
File Size : 48,7 Mb
Release : 2007-12-06
Category : Mathematics
ISBN : 9783540729600

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Advances in Metaheuristics for Hard Optimization by Patrick Siarry,Zbigniew Michalewicz Pdf

Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

Multi-Objective Optimization using Evolutionary Algorithms

Kalyanmoy Deb
Multi Objective Optimization using Evolutionary Algorithms Book PDF

Author : Kalyanmoy Deb
Publisher : John Wiley & Sons
Page : 540 pages
File Size : 55,6 Mb
Release : 2001-07-05
Category : Mathematics
ISBN : 047187339X

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Multi-Objective Optimization using Evolutionary Algorithms by Kalyanmoy Deb Pdf

Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.

Evolutionary Algorithms in Intelligent Systems

Alfredo Milani,Arturo Carpi,Valentina Poggioni
Evolutionary Algorithms in Intelligent Systems Book PDF

Author : Alfredo Milani,Arturo Carpi,Valentina Poggioni
Publisher : MDPI
Page : 144 pages
File Size : 45,7 Mb
Release : 2020-12-07
Category : Technology & Engineering
ISBN : 9783039436118

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Evolutionary Algorithms in Intelligent Systems by Alfredo Milani,Arturo Carpi,Valentina Poggioni Pdf

Evolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally hard optimization problems. With the widespread use of intelligent systems in recent years, evolutionary algorithms have been applied, beyond classical optimization problems, to AI system parameter optimization and the design of artificial neural networks and feature selection in machine learning systems. This volume will present recent results of applications of the most successful metaheuristics, from differential evolution and particle swarm optimization to artificial neural networks, loT allocation, and multi-objective optimization problems. It will also provide a broad view of the role and the potential of evolutionary algorithms as service components in Al systems.

Metaheuristics for Finding Multiple Solutions

Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend
Metaheuristics for Finding Multiple Solutions Book PDF

Author : Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend
Publisher : Springer Nature
Page : 322 pages
File Size : 46,7 Mb
Release : 2021-10-22
Category : Computers
ISBN : 9783030795535

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Metaheuristics for Finding Multiple Solutions by Mike Preuss,Michael G. Epitropakis,Xiaodong Li,Jonathan E. Fieldsend Pdf

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the nature-inspired “niching” effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

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

Vasant, Pandian M.
Meta Heuristics Optimization Algorithms in Engineering Business Economics and Finance Book PDF

Author : Vasant, Pandian M.
Publisher : IGI Global
Page : 735 pages
File Size : 44,8 Mb
Release : 2012-09-30
Category : Computers
ISBN : 9781466620872

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

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.

Theory and Principled Methods for the Design of Metaheuristics

Yossi Borenstein,Alberto Moraglio
Theory and Principled Methods for the Design of Metaheuristics Book PDF

Author : Yossi Borenstein,Alberto Moraglio
Publisher : Springer Science & Business Media
Page : 270 pages
File Size : 47,6 Mb
Release : 2013-12-19
Category : Computers
ISBN : 9783642332067

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Theory and Principled Methods for the Design of Metaheuristics by Yossi Borenstein,Alberto Moraglio Pdf

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Metaheuristics

El-Ghazali Talbi
Metaheuristics Book PDF

Author : El-Ghazali Talbi
Publisher : John Wiley & Sons
Page : 625 pages
File Size : 42,6 Mb
Release : 2009-05-27
Category : Computers
ISBN : 9780470496909

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Metaheuristics by El-Ghazali Talbi Pdf

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.

Evolutionary Algorithms for Solving Multi-Objective Problems

Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Evolutionary Algorithms for Solving Multi Objective Problems Book PDF

Author : Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen
Publisher : Springer Science & Business Media
Page : 810 pages
File Size : 41,7 Mb
Release : 2007-08-26
Category : Computers
ISBN : 9780387367972

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Evolutionary Algorithms for Solving Multi-Objective Problems by Carlos Coello Coello,Gary B. Lamont,David A. van Veldhuizen Pdf

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Metaheuristic and Evolutionary Computation: Algorithms and Applications

Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh
Metaheuristic and Evolutionary Computation Algorithms and Applications Book PDF

Author : Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh
Publisher : Springer Nature
Page : 830 pages
File Size : 47,8 Mb
Release : 2020-10-08
Category : Technology & Engineering
ISBN : 9789811575716

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Metaheuristic and Evolutionary Computation: Algorithms and Applications by Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh Pdf

This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.

Metaheuristics for Hard Optimization

Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Metaheuristics for Hard Optimization Book PDF

Author : Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Publisher : Springer Science & Business Media
Page : 372 pages
File Size : 41,6 Mb
Release : 2006-01-16
Category : Mathematics
ISBN : 9783540309666

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Metaheuristics for Hard Optimization by Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard Pdf

Contains case studies from engineering and operations research Includes commented literature for each chapter