Ergebnisse für: ant algorithms
Hier findest Du Bücher, die sich mit ant algorithms beschäftigen.
This book constitutes the refereed proceedings of the Third International Workshop on Ant Algorithms, ANTS 2002, held in Brussels, Belgium in September 2002.The 17 revised full papers, 11 short papers, and extended poster abstracts presented were carefully reviewed and selected from 52 submissions. ...
This book constitutes the refereed proceedings of the Third International Workshop on Ant Algorithms, ANTS 2002, held in Brussels, Belgium in September 2002.The 17 revised full papers, 11 short papers, and extended poster abstracts presented were carefully reviewed and selected from 52 submissions. ...
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 avai...
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they ...
This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental l...
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 avai...
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 avai...
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 “AN...
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 ...
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 ...
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 “AN...
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they ...
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they ...
This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental l...