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Ant Colony Optimization

Ant Colony Optimization PDF Author: Avi Ostfeld
Publisher: BoD – Books on Demand
ISBN: 9533071575
Category : Computers
Languages : en
Pages : 356

Book Description
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

Ant Colony Optimization PDF Author: Avi Ostfeld
Publisher: BoD – Books on Demand
ISBN: 9533071575
Category : Computers
Languages : en
Pages : 356

Book Description
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

Ant Colony Optimization PDF Author: Marco Dorigo
Publisher: MIT Press
ISBN: 9780262042192
Category : Computers
Languages : en
Pages : 324

Book Description
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

Ant Colony Optimization PDF Author: Helio Barbosa
Publisher: BoD – Books on Demand
ISBN: 9535110012
Category : Computers
Languages : en
Pages : 216

Book Description
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 and Applications

Ant Colony Optimization and Applications PDF Author: Stefka Fidanova
Publisher: Springer Nature
ISBN: 3030673804
Category : Technology & Engineering
Languages : en
Pages : 135

Book Description
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.

Theoretical and Practical Aspects of Ant Colony Optimization

Theoretical and Practical Aspects of Ant Colony Optimization PDF Author: Christian Blum
Publisher: IOS Press
ISBN: 9783898382823
Category : Ant algorithms
Languages : en
Pages : 298

Book Description
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 Constraint Programming

Ant Colony Optimization and Constraint Programming PDF Author: Christine Solnon
Publisher: John Wiley & Sons
ISBN: 1118618890
Category : Computers
Languages : en
Pages : 320

Book Description
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 Optimization and Swarm Intelligence

Ant Colony Optimization and Swarm Intelligence PDF Author: Marco Dorigo
Publisher: Springer
ISBN: 3540286462
Category : Mathematics
Languages : en
Pages : 445

Book Description
1 With its fourth edition, the ANTS series of workshops has changed its name. The original"ANTS-From Ant Colonies to Artificial Ants: International Workshop on Ant Algorithms" has become "ANTS - International Workshop on Ant Colony Optimization and Swarm Intelligence". This change is mainly due to the following reasons. First, the term "ant algorithms" was slower in spreading in the research community than the term "swarm intelligence", while at the same time research inso-called swarm robotics was the subject of increasing activity: it was therefore an obvious choice to substitute the term ant algorithms with the more accepted and used term swarm intelligence. Second, although swarm intelligence research has undoubtedly produced a 2 number of interesting and promising research directions, we think it is fair to say that its most successful strand is the one known as "ant colony optimization". Ant colony optimization, first introduced in the early 1990s as a novel tool for the approximate solution of discrete optimization problems, has recently seen an explosion in the number of its applications, both to academic and real-world problems, and is currently being extended to the realm of continuous optimization (a few papers on this subject being published in these proceedings). It is therefore a reasonable choice to have the term ant colony optimization as part of the workshop name

Ant Colony Optimization and Swarm Intelligence

Ant Colony Optimization and Swarm Intelligence PDF Author: Marco Dorigo
Publisher: Springer
ISBN: 3540384839
Category : Computers
Languages : en
Pages : 526

Book Description
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.

Ant Colony Optimization and Swarm Intelligence

Ant Colony Optimization and Swarm Intelligence PDF Author: Marco Dorigo
Publisher: Springer Science & Business Media
ISBN: 3540875263
Category : Computers
Languages : en
Pages : 430

Book Description
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.

Long Term Open Pit Planning by Ant Colony Optimization

Long Term Open Pit Planning by Ant Colony Optimization PDF Author: Javad Sattarvand
Publisher:
ISBN:
Category :
Languages : en
Pages : 129

Book Description