Multi-Objective Optimization - Evolutionary to Hybrid Framework (Paperback, Softcover reprint of the original 1st ed. 2018)

This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	December 2018
First published:	2018
Editors:	Jyotsna K Mandal • Somnath Mukhopadhyay • Paramartha Dutta
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	318
Edition:	Softcover reprint of the original 1st ed. 2018
ISBN-13:	978-981-13-4639-2
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	981-13-4639-9
Barcode:	9789811346392

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