Ant colony optimization /

Ant Colony Optimization (ACO) is the best example of how studies intended at understanding and modeling the behavior of ants and other social insects can inspire the development of computational algorithms for the solution of tough mathematical problems. Introduced by Marco Dorigo in his PhD thesis...

Full description

Bibliographic Details
Main Author: Pizzo, Julia, editor
Format:
Language:eng
Published: New Jersey, N.J. : Clanrye International, 2015
Subjects:
_version_ 1826459335631306752
author Pizzo, Julia, editor
author_facet Pizzo, Julia, editor
author_sort Pizzo, Julia, editor
collection OCEAN
description Ant Colony Optimization (ACO) is the best example of how studies intended at understanding and modeling the behavior of ants and other social insects can inspire the development of computational algorithms for the solution of tough mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced an enormous growth, reaching a position of an essential nature-inspired stochastic metaheuristic for optimization of critical problems. This book offers state-of-the-art ACO methods and covers various techniques, comprising of parallel implementations and applications, where current investments of ACO to varied areas, like traffic clog and discipline, structural optimization, manufacturing, and genomics have been demonstrated.
first_indexed 2024-03-05T14:04:56Z
format
id KOHA-OAI-TEST:511525
institution Universiti Teknologi Malaysia - OCEAN
language eng
last_indexed 2024-03-05T14:04:56Z
publishDate 2015
publisher New Jersey, N.J. : Clanrye International,
record_format dspace
spelling KOHA-OAI-TEST:5115252020-12-19T17:18:57ZAnt colony optimization / Pizzo, Julia, editor New Jersey, N.J. : Clanrye International,2015engAnt Colony Optimization (ACO) is the best example of how studies intended at understanding and modeling the behavior of ants and other social insects can inspire the development of computational algorithms for the solution of tough mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced an enormous growth, reaching a position of an essential nature-inspired stochastic metaheuristic for optimization of critical problems. This book offers state-of-the-art ACO methods and covers various techniques, comprising of parallel implementations and applications, where current investments of ACO to varied areas, like traffic clog and discipline, structural optimization, manufacturing, and genomics have been demonstrated.Includes bibliographical referencesAnt Colony Optimization (ACO) is the best example of how studies intended at understanding and modeling the behavior of ants and other social insects can inspire the development of computational algorithms for the solution of tough mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced an enormous growth, reaching a position of an essential nature-inspired stochastic metaheuristic for optimization of critical problems. This book offers state-of-the-art ACO methods and covers various techniques, comprising of parallel implementations and applications, where current investments of ACO to varied areas, like traffic clog and discipline, structural optimization, manufacturing, and genomics have been demonstrated.PSZJBLAnt algorithmsMathematical optimizationAlgorithmsURN:ISBN:9781632400611
spellingShingle Ant algorithms
Mathematical optimization
Algorithms
Pizzo, Julia, editor
Ant colony optimization /
title Ant colony optimization /
title_full Ant colony optimization /
title_fullStr Ant colony optimization /
title_full_unstemmed Ant colony optimization /
title_short Ant colony optimization /
title_sort ant colony optimization
topic Ant algorithms
Mathematical optimization
Algorithms
work_keys_str_mv AT pizzojuliaeditor antcolonyoptimization