Multi-objective Optimization: Evolutionary To Hybrid Framework
by Jyotsna K. Mandal 2021-01-06 14:21:06
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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 evolu... Read more

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.

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  • 9.25 X 6.1 X 0 in
  • 318
  • Springer Nature
  • August 29, 2018
  • English
  • 9789811314704
Dr. Jyotsna K. ​Mandal received his M.Tech. in Computer Science from the University of Calcutta and his Ph.D. from Jadavpur University in the field of Data Compression and Error Correction Technique...
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