Articles liés à Deterministic and Stochastic Models in Optimization...

Deterministic and Stochastic Models in Optimization Theory: Optimization, Optical Designing, Stability Analysis, Log-scaled Mutation, Genetic Algorithm - Couverture souple

Kuipo Kibindé, Jude; Tiwari, Bhupendra Nath; Gupta, Neeraj

 
9786202003759: Deterministic and Stochastic Models in Optimization Theory: Optimization, Optical Designing, Stability Analysis, Log-scaled Mutation, Genetic Algorithm
Couverture souple
ISBN 10 : 6202003758 ISBN 13 : 9786202003759
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

Optimization theory emerges as an integral part of applied mathematics in order to address complex scientific and engineering problems. Optical optimization is formulated mathematically by considering the corresponding focal length of the lens/ mirror as the objective function subject to object distance and lateral magnification. The stability domains of objective function are examined by multivariable calculus and eigenvalue analysis. Qualitative depictions of stability components are provided to enhance the comprehension of optical systems. This book gives criteria for the domains in searching the global optima. We discuss the notion of the intrinsic optical length, zoom-in, zoom-out, power, constrained and multicomponent optimizations. We propose an Enhanced Selection and Log-scaled Mutation Genetic Algorithm as a metaheuristic optimizer, which arises via the simulated annealing selection and adaptive log-scaled mutation schemes. A hybridization of deterministic and metaheuristic optimization emerges as a novel tool towards industrial applications. Validation on various objective functions reveals that our proposal offers improved convergence in realism of the Genetic Algorithm.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Optimization theory emerges as an integral part of applied mathematics in order to address complex scientific and engineering problems. Optical optimization is formulated mathematically by considering the corresponding focal length of the lens/ mirror as the objective function subject to object distance and lateral magnification. The stability domains of objective function are examined by multivariable calculus and eigenvalue analysis. Qualitative depictions of stability components are provided to enhance the comprehension of optical systems. This book gives criteria for the domains in searching the global optima. We discuss the notion of the intrinsic optical length, zoom-in, zoom-out, power, constrained and multicomponent optimizations. We propose an Enhanced Selection and Log-scaled Mutation Genetic Algorithm as a metaheuristic optimizer, which arises via the simulated annealing selection and adaptive log-scaled mutation schemes. A hybridization of deterministic and metaheuristic optimization emerges as a novel tool towards industrial applications. Validation on various objective functions reveals that our proposal offers improved convergence in realism of the Genetic Algorithm.

Biographie de l'auteur

Er. Jude Kuipo Kibindé is a communication network and security graduate, Dr. Bhupendra Nath Tiwari is a theoretical and mathematical scientist, Dr. Neeraj Gupta is an electrical engineer and Prof. Ninoslav Marina is an information theorist at UIST Ohrid, Macedonia. Our research interests encompass theoretical and mathematical aspects of S&T.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2017
Langue
anglais
ISBN 10 
6202003758
ISBN 13 
9786202003759
Reliure
Broché
Nombre de pages
132
Coordonnées du fabricant
non disponible
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