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Decision Science in Action: Theory and Applications of Modern Decision Analytic Optimisation

Deep, Kusum and Jain, Madhu and Salhi, Said, eds. (2019) Decision Science in Action: Theory and Applications of Modern Decision Analytic Optimisation. Asset Analytics . Springer, Singapore, 280 pp. ISBN 978-981-1308-59-8. E-ISBN 978-981-1308-60-4. (doi:10.1007/978-981-13-0860-4)

Abstract

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.

Item Type: Edited book
DOI/Identification number: 10.1007/978-981-13-0860-4
Uncontrolled keywords: decision science, business analytic, optimisation
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics > HA33 Management Science
Q Science > Operations Research - Theory
Divisions: Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Management Science
Faculties > Social Sciences > Kent Business School > Centre for Logistics and Heuristic Organisation (CLHO)
Depositing User: Said Salhi
Date Deposited: 16 Jul 2018 15:59 UTC
Last Modified: 30 Aug 2019 15:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67629 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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