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Titlebook: Decision Science in Action; Theory and Applicati Kusum Deep,Madhu Jain,Said Salhi Book 2019 Springer Nature Singapore Pte Ltd. 2019 Optimiz

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發(fā)表于 2025-3-21 18:40:04 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Decision Science in Action
副標(biāo)題Theory and Applicati
編輯Kusum Deep,Madhu Jain,Said Salhi
視頻videohttp://file.papertrans.cn/265/264268/264268.mp4
概述Provides practical and novel optimization techniques that can be adapted to a broad spectrum of applications ranging from Engineering to Finance.Discusses theoretical studies that underpin some of the
叢書(shū)名稱(chēng)Asset Analytics
圖書(shū)封面Titlebook: Decision Science in Action; Theory and Applicati Kusum Deep,Madhu Jain,Said Salhi Book 2019 Springer Nature Singapore Pte Ltd. 2019 Optimiz
描述.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 pro
出版日期Book 2019
關(guān)鍵詞Optimization Science; Π Fraction-based Optimization; Artificial Bee Colony Based Hyper-heuristic; Artif
版次1
doihttps://doi.org/10.1007/978-981-13-0860-4
isbn_softcover978-981-13-4520-3
isbn_ebook978-981-13-0860-4Series ISSN 2522-5162 Series E-ISSN 2522-5170
issn_series 2522-5162
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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An Artificial Bee Colony Based Hyper-heuristic for the Single Machine Order Acceptance and Scheduli space of heuristics, is developed to search the best heuristic from a set of heuristics residing at the lower level of hyper-heuristic. The proposed approach is compared with the state-of-the-art approaches. The computational results show that the integration of ABC algorithm into hyper-heuristic o
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Seismic Analysis of Multistoried Building with Optimized Damper Properties,echniques provide better optimized damper properties. It is observed that the optimized damper helps in significant reduction of the seismic response of the structure, thus justifying the need of optimized parameters of dampers.
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Book 2019linear 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 pro
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https://doi.org/10.1007/978-94-017-6561-9ctions mitigate these issues by introducing pseudorandomness in an otherwise truly random metaheuristic, for example, genetic algorithm. This paper illustrates the utility of . fractions by using them in two different optimizers, one deterministic and the other probabilistic. These optimizers are ap
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