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Titlebook: Engineering and Applied Sciences Optimization; Dedicated to the Mem Nikos D. Lagaros,Manolis Papadrakakis Book 2015 The Editor(s) (if appli

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书目名称Engineering and Applied Sciences Optimization
副标题Dedicated to the Mem
编辑Nikos D. Lagaros,Manolis Papadrakakis
视频video
概述Serves as a forum for scientists working in computational optimization.Brings together the scientific community working in the broader field of engineering and applied sciences optimization.Includes p
丛书名称Computational Methods in Applied Sciences
图书封面Titlebook: Engineering and Applied Sciences Optimization; Dedicated to the Mem Nikos D. Lagaros,Manolis Papadrakakis Book 2015 The Editor(s) (if appli
描述.The chapters which appear in this volume are selected studies presented at the First International Conference on Engineering and Applied Sciences Optimization (OPT-i), Kos, Greece, 4-6 June 2014 and works written by friends, former colleagues and students of the late Professor M. G. Karlaftis; all in the area of optimization that he loved and published so much in himself. The subject areas represented here range from structural optimization, logistics, transportation, traffic and telecommunication networks to operational research, metaheuristics, multidisciplinary and multiphysics design optimization, etc..This volume is dedicated to the life and the memory of Professor Matthew G. Karlaftis, who passed away a few hours before he was to give the opening speech at OPT-i. All contributions reflect the warmth and genuine friendship which he enjoyed from his associates and show how much his scientific contribution has been appreciated. He will be greatly missed and it is hoped that this volume will be received as a suitable memorial to his life and achievements..
出版日期Book 2015
关键词Gradient Based and Derivative Free Optimization Algorithms; K; G; Karlaftis; Logistics, Transportation;
版次1
doihttps://doi.org/10.1007/978-3-319-18320-6
isbn_softcover978-3-319-36465-0
isbn_ebook978-3-319-18320-6Series ISSN 1871-3033 Series E-ISSN 2543-0203
issn_series 1871-3033
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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https://doi.org/10.1007/978-3-319-63820-1improved methodological framework is suggested for the optimization of car-following models. Machine learning techniques, such as classification, locally weighted regression (loess) and clustering, are innovatively integrated. In this chapter, validation of the proposed methods is demonstrated on da
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Defining Enterprise Risk Management,The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size
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A Model of Instability in Asset Marketse on both displacements and accelerations. But for acceleration objective, a small benefit for accelerations can be seen although the optimum mass of TMD is very heavy according to displacement objective.
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