Nature-inspired metaheuristic algorithms : solving real world engineering problems /

This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United N...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Bansal, Sulabh (Editor), Tripathi, Aprna (Editor), Srivastava, Shilpa (Editor), Vuppuluri, Prem Prakash (Editor)
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, [2025]
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities.This book: Discusses load balancing and demand response using nature-inspired optimization techniques Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Physical Description:1 online resource (402 pages) illustrations
Audience:Academic, Postgraduate, and Undergraduate Advanced
ISBN:9781003612858
1003612857
9781040344873
1040344879
9781040344897
1040344895