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Decision science in action = theory ...

Deep, Kusum.

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Decision science in action = theory and applications of modern decision analytic optimisation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Decision science in action/ edited by Kusum Deep, Madhu Jain, Said Salhi.
Reminder of title:	theory and applications of modern decision analytic optimisation /
other author:	Deep, Kusum.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	vii, 276 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Decision making. -
Online resource:	https://doi.org/10.1007/978-981-13-0860-4
ISBN:	9789811308604

Decision science in action = theory and applications of modern decision analytic optimisation /
Decision science in actiontheory and applications of modern decision analytic optimisation /[electronic resource] :edited by Kusum Deep, Madhu Jain, Said Salhi. - Singapore :Springer Singapore :2019. - vii, 276 p. :ill., digital ;24 cm. - Asset analytics, performance and safety management,2522-5162. - Asset analytics, performance and safety management..

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book's twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja-Bretones-Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot's stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.

ISBN: 9789811308604

Standard No.: 10.1007/978-981-13-0860-4doiSubjects--Topical Terms:

517204
Decision making.

LC Class. No.: QA279.4

Dewey Class. No.: 519.542

Decision science in action = theory and applications of modern decision analytic optimisation /
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245 0 0 $a Decision science in action $h [electronic resource] : $b theory and applications of modern decision analytic optimisation / $c edited by Kusum Deep, Madhu Jain, Said Salhi.
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520 $a This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book's twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja-Bretones-Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot's stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.
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