Ant Colony Optimization
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 i...
שמור ב:
| פורמט: | Online |
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| שפה: | אנגלית |
| יצא לאור: |
IntechOpen
2021
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| נושאים: | |
| גישה מקוונת: | ONIX_20210420_9789535110019_1787 |
| תגים: |
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
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| _version_ | 1869523000695455744 |
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| collection | Directory of Open Access Books |
| 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. |
| format | Online |
| id | doab-20.500.12854ir-66429 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | ojs |
| spelling | doab-20.500.12854ir-664292024-04-14T10:29:19Z Ant Colony Optimization Barbosa, Helio J.C. Computer programming / software development thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering 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. 2021-04-20T15:43:00Z 2021-04-20T15:43:00Z 2013 book ONIX_20210420_9789535110019_1787 9789535110019 9789535157175 https://directory.doabooks.org/handle/20.500.12854/66429 eng image/jpeg n/a https://www.intechopen.com/books https://mts.intechopen.com/storage/books/3123/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/3423 10.5772/3423 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789535110019 9789535157175 IntechOpen 214 open access |
| spellingShingle | Computer programming / software development thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering 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 | Computer programming / software development thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering |
| topic_facet | Computer programming / software development thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering |
| url | ONIX_20210420_9789535110019_1787 |