Ant Colony Optimization

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Ant Colony Optimization

Marco Dorigo,Thomas Stutzle
Ant Colony Optimization Book PDF

Author : Marco Dorigo,Thomas Stutzle
Publisher : MIT Press
Page : 324 pages
File Size : 50,7 Mb
Release : 2004-06-04
Category : Computers
ISBN : 0262042193

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Ant Colony Optimization by Marco Dorigo,Thomas Stutzle Pdf

An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.

Ant Colony Optimization

Helio Barbosa
Ant Colony Optimization Book PDF

Author : Helio Barbosa
Publisher : BoD – Books on Demand
Page : 216 pages
File Size : 47,5 Mb
Release : 2013-02-20
Category : Computers
ISBN : 9789535110019

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Ant Colony Optimization by Helio Barbosa Pdf

Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling the behavior of ants and other social insects can provide inspiration for the development of computational algorithms for the solution of difficult mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced a tremendous growth, standing today as an important nature-inspired stochastic metaheuristic for hard optimization problems. This book presents state-of-the-art ACO methods and is divided into two parts: (I) Techniques, which includes parallel implementations, and (II) Applications, where recent contributions of ACO to diverse fields, such as traffic congestion and control, structural optimization, manufacturing, and genomics are presented.

Ant Colony Optimization

Avi Ostfeld
Ant Colony Optimization Book PDF

Author : Avi Ostfeld
Publisher : BoD – Books on Demand
Page : 356 pages
File Size : 44,5 Mb
Release : 2011-02-04
Category : Computers
ISBN : 9789533071572

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Ant Colony Optimization by Avi Ostfeld Pdf

Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.

Ant Colony Optimization and Constraint Programming

Christine Solnon
Ant Colony Optimization and Constraint Programming Book PDF

Author : Christine Solnon
Publisher : John Wiley & Sons
Page : 226 pages
File Size : 40,5 Mb
Release : 2013-03-04
Category : Computers
ISBN : 9781118618899

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Ant Colony Optimization and Constraint Programming by Christine Solnon Pdf

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages. The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems. The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

Ant Colony Optimization and Swarm Intelligence

Marco Dorigo,Mauro Birattari,Christian Blum,Maurice Clerc,Thomas Stützle,Alan Winfield
Ant Colony Optimization and Swarm Intelligence Book PDF

Author : Marco Dorigo,Mauro Birattari,Christian Blum,Maurice Clerc,Thomas Stützle,Alan Winfield
Publisher : Springer
Page : 416 pages
File Size : 48,6 Mb
Release : 2008-09-20
Category : Computers
ISBN : 9783540875277

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Ant Colony Optimization and Swarm Intelligence by Marco Dorigo,Mauro Birattari,Christian Blum,Maurice Clerc,Thomas Stützle,Alan Winfield Pdf

The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the ?rst edition of ANTS was titled “ANTS’98 – From Ant Colonies to Arti?cial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the ?rst swarm intelligence algorithm to go beyond a pure scienti?c interest and to enter the realm of real-world applications. Interestingly, in the ten years after the ?rst edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence ?eld is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - telligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003,the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing ?eld, we are currently establishingacooperationagreementbetweenIEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.

Handbook of Swarm Intelligence

Bijaya Ketan Panigrahi,Yuhui Shi,Meng-Hiot Lim
Handbook of Swarm Intelligence Book PDF

Author : Bijaya Ketan Panigrahi,Yuhui Shi,Meng-Hiot Lim
Publisher : Springer Science & Business Media
Page : 544 pages
File Size : 49,5 Mb
Release : 2011-02-04
Category : Technology & Engineering
ISBN : 9783642173905

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Handbook of Swarm Intelligence by Bijaya Ketan Panigrahi,Yuhui Shi,Meng-Hiot Lim Pdf

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Ant Colony Optimization and Applications

Stefka Fidanova
Ant Colony Optimization and Applications Book PDF

Author : Stefka Fidanova
Publisher : Springer Nature
Page : 135 pages
File Size : 52,6 Mb
Release : 2021-02-27
Category : Technology & Engineering
ISBN : 9783030673802

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Ant Colony Optimization and Applications by Stefka Fidanova Pdf

This book is interesting and full of new ideas. It provokes the curiosity of the readers. The book targets both researchers and practitioners. The students and the researchers will acquire knowledge about ant colony optimization and its possible applications as well as practitioners will find new ideas and solutions of their combinatorial optimization and decision-making problems. Ant colony optimization is between the best method for solving difficult optimization problems arising in real life and industry. It has obtained distinguished results on some applications with very restrictive constraints. The reader will find theoretical aspects of ant method as well as applications on a variety of problems. The following applications could be mentioned: multiple knapsack problem, which is an important economical problem; grid scheduling problem; GPS surveying problem; E. coli cultivation modeling; wireless sensor network positioning; image edges detection; workforce planning.

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Muhammet Ünal,Ayça Ak,Vedat Topuz,Hasan Erdal
Optimization of PID Controllers Using Ant Colony and Genetic Algorithms Book PDF

Author : Muhammet Ünal,Ayça Ak,Vedat Topuz,Hasan Erdal
Publisher : Springer
Page : 88 pages
File Size : 51,5 Mb
Release : 2012-09-13
Category : Technology & Engineering
ISBN : 9783642329005

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Optimization of PID Controllers Using Ant Colony and Genetic Algorithms by Muhammet Ünal,Ayça Ak,Vedat Topuz,Hasan Erdal Pdf

Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.

Theoretical and Practical Aspects of Ant Colony Optimization

Christian Blum
Theoretical and Practical Aspects of Ant Colony Optimization Book PDF

Author : Christian Blum
Publisher : IOS Press
Page : 298 pages
File Size : 48,6 Mb
Release : 2004
Category : Ant algorithms
ISBN : 3898382826

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Theoretical and Practical Aspects of Ant Colony Optimization by Christian Blum Pdf

Combinatorial optimization problems are of high academical and practical importance. Unfortunately, many of them belong to the class of NP-hard problems and are therefore intractable. In other words, as their dimension increases, the time needed by exact methods to find an optimal solution grows exponentially. Metaheuristics are approximate methods for attacking these problems. An approximate method is a technique that is applied in order to find a good enough solution in a reasonable amount of time. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, and ant colony optimization (ACO), the subject of this book. The contributions of this book to ACO research are twofold. First, some new theoretical results are proven that improve our understanding of how ACO works. Second, a new framework for ACO algorithms is proposed that is shown to perform at the state-of-the-art level on some important combinatorial optimization problems such as the k-cardinality tree problem and the group shop scheduling problem, which is a general shop scheduling problem that includes among others the well-known job shop scheduling and the open shop scheduling problems.

Ant Colony Optimization and Swarm Intelligence

Marco Dorigo,Luca Maria Gambardella,Mauro Birattari,Alcherio Martinoli,Riccardo Poli,Thomas Stützle
Ant Colony Optimization and Swarm Intelligence Book PDF

Author : Marco Dorigo,Luca Maria Gambardella,Mauro Birattari,Alcherio Martinoli,Riccardo Poli,Thomas Stützle
Publisher : Springer
Page : 526 pages
File Size : 40,7 Mb
Release : 2006-08-29
Category : Computers
ISBN : 9783540384830

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Ant Colony Optimization and Swarm Intelligence by Marco Dorigo,Luca Maria Gambardella,Mauro Birattari,Alcherio Martinoli,Riccardo Poli,Thomas Stützle Pdf

This book constitutes the refereed proceedings of the 5th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2006, held in Brussels, Belgium, in September 2006. The 27 revised full papers, 23 revised short papers, and 12 extended abstracts presented were carefully reviewed and selected from 115 submissions.

Decision Tree and Ensemble Learning Based on Ant Colony Optimization

Jan Kozak
Decision Tree and Ensemble Learning Based on Ant Colony Optimization Book PDF

Author : Jan Kozak
Publisher : Springer
Page : 159 pages
File Size : 45,9 Mb
Release : 2018-06-20
Category : Technology & Engineering
ISBN : 9783319937526

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Decision Tree and Ensemble Learning Based on Ant Colony Optimization by Jan Kozak Pdf

This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.

Ant Colony Optimization and Swarm Intelligence

Directeur de Recherches Du Fnrs Marco Dorigo,Marco Dorigo,Mauro Birattari,Christian Blum,Luca M. Gambardella,Francesco Mondada,Thomas Stützle
Ant Colony Optimization and Swarm Intelligence Book PDF

Author : Directeur de Recherches Du Fnrs Marco Dorigo,Marco Dorigo,Mauro Birattari,Christian Blum,Luca M. Gambardella,Francesco Mondada,Thomas Stützle
Publisher : Springer Science & Business Media
Page : 445 pages
File Size : 48,9 Mb
Release : 2004-08-19
Category : Computers
ISBN : 9783540226727

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Ant Colony Optimization and Swarm Intelligence by Directeur de Recherches Du Fnrs Marco Dorigo,Marco Dorigo,Mauro Birattari,Christian Blum,Luca M. Gambardella,Francesco Mondada,Thomas Stützle Pdf

This book constitutes the refereed proceedings of the 4th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2004, held in Brussels, Belgium in September 2004. The 22 revised full papers, 19 revised short papers, and 9 poster abstracts presented were carefully reviewed and selected from 79 papers submitted. The papers are devoted to theoretical and foundational aspects of ant algorithms, ant colony optimization and swarm intelligence and deal with a broad variety of optimization applications in networking and operations research.

Recent Advances on Hybrid Intelligent Systems

Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Recent Advances on Hybrid Intelligent Systems Book PDF

Author : Oscar Castillo,Patricia Melin,Janusz Kacprzyk
Publisher : Springer
Page : 572 pages
File Size : 46,5 Mb
Release : 2012-09-14
Category : Technology & Engineering
ISBN : 9783642330216

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Recent Advances on Hybrid Intelligent Systems by Oscar Castillo,Patricia Melin,Janusz Kacprzyk Pdf

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.

Fuzzy Engineering and Operations Research

Bing-Yuan Cao,Xiang-Jun Xie
Fuzzy Engineering and Operations Research Book PDF

Author : Bing-Yuan Cao,Xiang-Jun Xie
Publisher : Springer Science & Business Media
Page : 608 pages
File Size : 46,9 Mb
Release : 2012-06-30
Category : Technology & Engineering
ISBN : 9783642285929

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Fuzzy Engineering and Operations Research by Bing-Yuan Cao,Xiang-Jun Xie Pdf

“Fuzzy Engineering and Operations Research” is the edited outcome of the 5th International Conference on Fuzzy Information and Engineering (ICFIE2011) held during Oct. 15-17, 2011 in Chengdu, China and by the 1st academic conference in establishment of Guangdong Province Operations Research Society (GDORSC) held on Oct. 20, 2011 in Guangzhou, China. The 5th ICFIE2011, built on the success of previous conferences, and the GDORC, first held, are major Symposiums, respectively, for scientists, engineers practitioners and Operation Research (OR) researchers presenting their updated results, developments and applications in all areas of fuzzy information and engineering and OR. It aims to strengthen relations between industry research laboratories and universities, and to create a primary symposium for world scientists in Fuzziology and OR fields. The book contains 62 papers and is divided into five main parts: “Fuzzy Optimization, Logic and Information”, “The mathematical Theory of Fuzzy Systems”, “Fuzzy Engineering Applications and Soft Computing Methods”, “OR and Fuzziology” and “Guess and Review”.

Ant Colony Optimization Algorithms

Fouad Sabry
Ant Colony Optimization Algorithms Book PDF

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
Page : 139 pages
File Size : 45,6 Mb
Release : 2023-07-01
Category : Computers
ISBN : PKEY:6610000480180

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Ant Colony Optimization Algorithms by Fouad Sabry Pdf

What Is Ant Colony Optimization Algorithms The Ant Colony Optimization Algorithm, also known as ACO, is a probabilistic technique for addressing computational problems in the fields of computer science and operations research. These problems can be boiled down to the task of finding good paths through graphs. The behavior of natural ants served as inspiration for the development of multi-agent systems, which are represented by artificial ants. The communication of biological ants through the use of pheromones is frequently the major paradigm that is adopted. Combinations of artificial ants and local search algorithms have become the technique of choice for several optimization tasks involving some kind of graph, such as internet routing and vehicle routing. This is because these combinations are able to find optimal solutions more quickly than traditional methods. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Ant colony optimization algorithms Chapter 2: Job-shop scheduling Chapter 3: Open-shop scheduling Chapter 4: Quadratic assignment problem Chapter 5: Generalized assignment problem Chapter 6: Set cover problem Chapter 7: Partition problem Chapter 8: Bankruptcy prediction Chapter 9: Protein-protein interaction Chapter 10: Protein folding (II) Answering the public top questions about ant colony optimization algorithms. (III) Real world examples for the usage of ant colony optimization algorithms in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of ant colony optimization algorithms. What is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.