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Multi-Objective Optimization

Evolutionary to Hybrid Framework

Paramartha Dutta

Jyotsna K. Mandal

Somnath Mukhopadhyay

Jezik

Angleščina

Knjiga Trda

Koda Libristo: 19690548

Založba Springer Verlag, Singapore, avgust 2018

This book brings together the latest findings on efficient solutions of multi/many-objective optimiz... Celoten opis

Koda Libristo: 19690548

377 b

155.51 €

Na zalogi pri dobavitelju Odposlali bomo v 10-13 dneh

30 dni za vračilo blaga

Drugi so kupili tudi

Januar - April 1945 Maximilian Gschaid

Trda

145.61 €

Ma Cousine Pot-Au-Feu Leon De Tinseau

Mehka

14.04 €

Mathematikunterricht inklusiv gestalten Angelika Bikner-Ahsbahs

Mehka

26.77 €

Requiem, Op.48 Gabriel Urbain Faure

Mehka

12.12 €

Tueurs a gags Jean-Pierre Martinez

Mehka

12.22 €

Rage, Biographie Et Travaux de Pasteur: Notions Generales Sur La Rage Consideree Portanier

Mehka

20.20 €

Junior plus 4 guide pédagogique Inmaculada Saracibar

Mehka

21.31 €

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.