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Titlebook: Recent Advances in Computational Optimization; Results of the Works Stefka Fidanova Book 2018 Springer International Publishing AG 2018 Com

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书目名称Recent Advances in Computational Optimization
副标题Results of the Works
编辑Stefka Fidanova
视频video
概述Addresses important real-world problems, like parameter settings for controlling processes in a bioreactor and control of ethanol production.Constitutes a comprehensive collection of extended contribu
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Recent Advances in Computational Optimization; Results of the Works Stefka Fidanova Book 2018 Springer International Publishing AG 2018 Com
描述.This book presents new optimization approaches and methods and their application in real-world and industrial problems, and demonstrates how many of the problems arising in engineering, economics and other domains can be formulated as optimization problems. Constituting a comprehensive collection of extended contributions from the 9th International Workshop on Computational Optimization (WCO) held in Gdansk, Poland, September 11–14, 2016, the book discusses important applications such as job scheduling, wildfire modeling, parameter settings for controlling different processes, capital budgeting, data mining, finding the location of sensors in a given network, identifying the conformation of molecules, algorithm correctness, decision support system, and computer memory management. Further, it shows how to develop algorithms for these based on new intelligent methods like evolutionary computations, ant colony optimization and constraint programming..The book is a valuable resource for researchers and practitioners alike..
出版日期Book 2018
关键词Computational Intelligence; Algorithms for Problems; Metaheuristic Methods; Intelligent Systems; WCO 201
版次1
doihttps://doi.org/10.1007/978-3-319-59861-1
isbn_softcover978-3-319-86720-5
isbn_ebook978-3-319-59861-1Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer International Publishing AG 2018
The information of publication is updating

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Sequential Predictive Scheduling in Partitioned Data Domains,. We explore the effects of reducing complexity by partitioning the data domain of the optimization problem for a sequential approach that integrates energy models for constraint handling directly into the optimization process. We explore the effects of different partitioning schemes and evaluate th
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