02742nam a22005415i 4500 978-981-99-7227-2 DE-He213 20251030111428.0 cr nn 008mamaa 240215s2024 si | s |||| 0|eng d 9789819972272 978-981-99-7227-2 10.1007/978-981-99-7227-2 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Applications of Ant Colony Optimization and its Variants [electronic resource] : Case Studies and New Developments / edited by Nilanjan Dey. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. IX, 229 p. 87 illus., 68 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Springer Tracts in Nature-Inspired Computing, 2524-5538 Ant Colony Optimization -- Advancements in Rank-based Ant System -- Exploring Ant Colony Optimization for Feature Selection: A Comprehensive Review -- Diagnosis Support for Diabetes with Ant Colony Optimization -- Opposed Pheromones Ant Colony Optimization for Property Identification of Nonlinear Structures. This book explains the basic ideas behind several variants of ant colony optimization (ACO) and shows how they may be used in real-world settings like manufacturing, engineering design, and health care. Marco Dorigo proposed ACO for the first time, and it has been used to solve a variety of optimization problems. This book presents the latest developments of ACO. Computational intelligence. 64052 Mathematical optimization. 65522 Artificial intelligence. 58441 Computational Intelligence. 64052 Optimization. 65528 Artificial Intelligence. 58441 Dey, Nilanjan. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819972265 Printed edition: 9789819972289 Printed edition: 9789819972296 Springer Tracts in Nature-Inspired Computing, 2524-5538 71076 https://doi.org/10.1007/978-981-99-7227-2 ZDB-2-INR ZDB-2-SXIT 57651 57651