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Ant Colony Optimization

Ant Colony Optimization ebook ISBN: 9780262042192
Publisher: MIT Press
Author: Marco Dorigo,Directeur de Recherches Du Fnrs Marco Dorigo,Thomas Stützle
Number of Pages: 305 
File: ant-colony-optimization.pdf
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Summary:

From real to artificial ants - The ant colony optimization metaheuristic - Ant colony optimization algorithms for the traveling salesman problem - Ant colony optimization theory - Ant colony optimization for NP-Hard problems - AntNet : an ACO algorithm for data network routing - Conclusions and prospects for the future.

Ant Colony Optimization and Swarm Intelligence

Ant Colony Optimization and Swarm Intelligence ebook ISBN: 3540384820
Publisher: Springer Science & Business Media
Author: Marco Dorigo,Luca Maria Gambardella,Mauro Birattari,Alcherio Martinoli,Riccardo Poli,Thomas Stützle
Number of Pages: 526 
File: ant-colony-optimization-and-swarm-intelligence.pdf
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Summary:

ANTS – The International Workshop on Ant Colony Optimization and Swarm Intelligence is now at its ?fth edition. The series started in 1998 with the - ganization of ANTS 1998. At that time the goal was to gather in a common meeting those researchers interested in ant colony optimization: more than 50 researchers from around the world joined for the ?rst time in Brussels, Belgium, to discuss ant colony optimization and swarm intelligence related research. A selectionofthebest paperspresentedatthe workshopwaspublished asa special issue of the Future Generation Computer Systems journal (Vol. 16, No. 8, 2000). Two years later, ANTS 2000, organized again in Brussels, attracted more than 70 participants. The 41 extended abstracts presented as talks or posters at the workshopwere collected in a booklet distributed to participants, and a selection of the best papers was published as a special section of the IEEE Transactions on Evolutionary Computation (Vol. 6, No. 4, 2002). After these ?rst two successful editions, it was decided to make of ANTS a seriesofbiannualeventswitho?cialworkshopproceedings.Thethirdandfourth editions were organized in September 2002 and September 2004, respectively. Proceedings were published by Springer within the Lecture Notes in Computer Science (LNCS) series. The proceedings of ANTS 2002, LNCS Volume 2463, contained 36 contri- tions: 17 full papers, 11 short papers, and 8 extended abstracts,selected out of a total of 52 submissions. Those of ANTS 2004, LNCS Volume 3172, contained 50 contributions:22 full papers, 19 shortpapers, and 9 extended abstracts,selected out of a total of 79 submissions.

Inside an Ant Colony

Inside an Ant Colony ebook ISBN: 9780516263656
Publisher: Childrens Press
Author: Allan Fowler
Number of Pages: 31 
File: inside-an-ant-colony.pdf
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Summary:

Describes how these social insects live and work together in organized communities that are like bustling cities.

Ant Colonies

Ant Colonies ebook ISBN: 1477703721
Publisher: The Rosen Publishing Group, Inc
Author: Louise Spilsbury,Richard Spilsbury
Number of Pages: 32 
File: ant-colonies.pdf
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Summary:

Working together as a group is vital for the tiny ant. Though vulnerable on their own, as a colony of hundreds or even millions they are able to find food, care for their young, and defend their homes from much larger attackers. Readers will discover a new world beneath their feet through exciting, accessible text.

Theoretical and Practical Aspects of Ant Colony Optimization

Theoretical and Practical Aspects of Ant Colony Optimization ebook ISBN: 9783898382823
Publisher: IOS Press
Author: Christian Blum
Number of Pages: 280 
File: theoretical-and-practical-aspects-of-ant-colony-optimization.pdf
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Summary:

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.

Handbook of Ant Colony

Handbook of Ant Colony ebook ISBN: 9781781543078
Publisher:
Author: Ignacio José
Number of Pages: 300 
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Summary:

The complex social behaviours of ants have been much studied by science, and computer scientists are now finding that these behaviour patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behaviour, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization, the most successful and widely recognized algorithmic technique based on ant behaviour. 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 Ant Colony

The Ant Colony ebook ISBN: 0007381018
Publisher: HarperCollins UK
Author: Jenny Valentine
Number of Pages: 224 
File: the-ant-colony.pdf
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Summary:

An irresistible novel from Guardian-award-winning novelist, Jenny Valentine.

Mighty Ants

Mighty Ants ebook ISBN: 1634402782
Publisher: Red Chair Press
Author: Wiley Blevins,Alice Boynton
Number of Pages: 32 
File: mighty-ants.pdf
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Summary:

The mighty ant has been around since the age of dinosaurs. These hard-working insects can be found on every continent except Antarctica. Readers will discover how ants work as a team and why they've been able to survive so long as they explore an ant colony.

An Ant's Colony

An Ant's Colony ebook ISBN: 1502620774
Publisher: Cavendish Square Publishing, LLC
Author: Erika de Nijs
Number of Pages: 24 
File: an-ant-s-colony.pdf
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Summary:

These muscular members of the insect world are capable of moving large objects, whether food or building material, in an organized and cooperative fashion. This book provides a view of the layout of a belowground colony and looks at the different environments that various species of ants call home.

A Colony of Ants and Other Insect Groups

A Colony of Ants and Other Insect Groups ebook ISBN: 1406239534
Publisher: Raintree
Author: Anna Claybourne
Number of Pages: 48 
File: a-colony-of-ants-and-other-insect-groups.pdf
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Summary:

Describes how ants (and other insects) function in colonies.

Ant Colony Optimization and Swarm Intelligence

Ant Colony Optimization and Swarm Intelligence ebook ISBN: 3540226729
Publisher: Springer Science & Business Media
Author: Directeur de Recherches Du Fnrs Marco Dorigo,Marco Dorigo,Mauro Birattari,Christian Blum,Luca M. Gambardella,Francesco Mondada,Thomas Stützle
Number of Pages: 434 
File: ant-colony-optimization-and-swarm-intelligence.pdf
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Summary:

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.

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms ebook ISBN: 3642329004
Publisher: Springer
Author: Muhammet Ünal,Ayça Ak,Vedat Topuz,Hasan Erdal
Number of Pages: 88 
File: optimization-of-pid-controllers-using-ant-colony-and-genetic-algorithms.pdf
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Summary:

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.

Ant Colonies

Ant Colonies ebook ISBN: 9781611220230
Publisher: Nova Science Pub Incorporated
Author: Emily C. Sun
Number of Pages: 274 
File: ant-colonies.pdf
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Summary:

Ant colony optimisation is a population-based general-search technique that can be used for the solution of difficult combinatorial problems. Ant colony optimisation uses the knowledge-reinforcing mechanism used by real-life ants while traversing possible paths in search of food, depositing a chemical substance (called pheromone), en-route and subsequently forming trails which can then be followed by other ants in the colony. With its strong mathematical foundation and its simplicity of use, ant colony optimisation provides an alternative method to routing optimisations with a wide range of applications. This book presents topical research in the study of ant colonies, their behaviour and application in computer technologies.

Ant Colony Optimization

Ant Colony Optimization ebook ISBN: 9533071575
Publisher: BoD – Books on Demand
Author: Avi Ostfeld
Number of Pages: 354 
File: ant-colony-optimization.pdf
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Summary:

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

Ant Colony Optimization and Constraint Programming ebook ISBN: 1118618890
Publisher: John Wiley & Sons
Author: Christine Solnon
Number of Pages: 320 
File: ant-colony-optimization-and-constraint-programming.pdf
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Summary:

Ant colony optimization is a metaheuristic which has beensuccessfully applied to a wide range of combinatorial optimizationproblems. The author describes this metaheuristic and studies itsefficiency for solving some hard combinatorial problems, with aspecific focus on constraint programming. The text is organizedinto three parts. The first part introduces constraint programming, which provideshigh level features to declaratively model problems by means ofconstraints. It describes the main existing approaches for solvingconstraint satisfaction problems, including complete tree searchapproaches and metaheuristics, and shows how they can be integratedwithin constraint programming languages. The second part describes the ant colony optimizationmetaheuristic and illustrates its capabilities on differentconstraint satisfaction problems. The third part shows how the ant colony may be integrated within aconstraint programming language, thus combining the expressivepower of constraint programming languages, to describe problems ina declarative way, and the solving power of ant colony optimizationto efficiently solve these problems.

Ant Colony

Ant Colony ebook ISBN:
Publisher: Drawn and Quarterly
Author: Michael DeForge
Number of Pages: 112 
File: ant-colony.pdf
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Summary:

Follows the strange exploits of a handful of black ants in a colony at war with a nearby colony of red ants.

Ant Colony Optimization Algorithms

Ant Colony Optimization Algorithms ebook ISBN: 9781983818370
Publisher: Createspace Independent Publishing Platform
Author: Gerardus Blokdyk
Number of Pages: 132 
File: ant-colony-optimization-algorithms.pdf
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Summary:

What other areas of the organization might benefit from the Ant colony optimization algorithms team's improvements, knowledge, and learning? Whats the best design framework for Ant colony optimization algorithms organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant? What are the Key enablers to make this Ant colony optimization algorithms move? Does Ant colony optimization algorithms analysis isolate the fundamental causes of problems? Is the Ant colony optimization algorithms process severely broken such that a re-design is necessary? Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role... In EVERY company, organization and department. Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Ant colony optimization algorithms investments work better. This Ant colony optimization algorithms All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Ant colony optimization algorithms Self-Assessment. Featuring 697 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Ant colony optimization algorithms improvements can be made. In using the questions you will be better able to: - diagnose Ant colony optimization algorithms projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Ant colony optimization algorithms and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Ant colony optimization algorithms Scorecard, you will develop a clear picture of which Ant colony optimization algorithms areas need attention. Your purchase includes access details to the Ant colony optimization algorithms self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Decision Tree and Ensemble Learning Based on Ant Colony Optimization

Decision Tree and Ensemble Learning Based on Ant Colony Optimization ebook ISBN: 3319937529
Publisher: Springer
Author: Jan Kozak
Number of Pages: 159 
File: decision-tree-and-ensemble-learning-based-on-ant-colony-optimization.pdf
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Summary:

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.

How Arnie Saved the Ant Colony on Merkel Mountain

How Arnie Saved the Ant Colony on Merkel Mountain ebook ISBN: 9781717575357
Publisher: Createspace Independent Publishing Platform
Author: Amber Behnke
Number of Pages: 44 
File: how-arnie-saved-the-ant-colony-on-merkel-mountain.pdf
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Summary:

The setting for this story is on beautiful Merkel Mountain that sits above the small town of Sylacauga, located in Central Alabama. There are hundreds of trees and lots of vegetation on Merkel Mountain. The soil is mostly red clay with embedded large rocks and the moist air on the mountain makes a perfect place for the ant colony. And where there are ants, there is probably an anteater nearby. This is a whimsical story about a young ant named Arnie who is determined to save the ant colony from a threatening anteater. He and his pet Rollo find a clever way to rid the anteater from Merkel Mountain forever. A delightful story from start to finish and great entertainment for the entire family.