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Recent advances in computational opt...

(1998 :)

Recent advances in computational optimizationresults of the Workshop on "Computational Optimization" and "Numerical Search and Optimization" 2018 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Recent advances in computational optimizationedited by Stefka Fidanova.
其他題名:	results of the Workshop on "Computational Optimization" and "Numerical Search and Optimization" 2018 /
其他作者:	Fidanova, Stefka.
團體作者:
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	x, 237 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Mathematical optimization
電子資源:	https://doi.org/10.1007/978-3-030-22723-4
ISBN:	9783030227234$q(electronic bk.)

Recent advances in computational optimizationresults of the Workshop on "Computational Optimization" and "Numerical Search and Optimization" 2018 /
Recent advances in computational optimizationresults of the Workshop on "Computational Optimization" and "Numerical Search and Optimization" 2018 /[electronic resource] :edited by Stefka Fidanova. - Cham :Springer International Publishing :2020. - x, 237 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,8381860-949X ;. - Studies in computational intelligence ;v. 216..

Preface -- Organization -- Chapter 1. Developing a Method for Measuring the Failover Times of First Hop Redundancy within Video Networks -- Chapter 2. Desktop application developed by open source tools for optimizations in cases of natural hazards and ﬁeld response. Chapter 3. Data optimizations on Kresna Fire (2017) as inputs for WFA simulations -- Chpater 4. Solving Sorting of Rolling Stock Problems utilizing pseudochain structures in Graphs, etc.

The book presents a comprehensive collection of extended contributions from the Workshops on Computational Optimization and Numerical Search and Optimization 2018. Our everyday life is unthinkable without optimization as we try to minimize our effort while maximizing profit. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. The book discusses recent advances in computational optimization to address important real-world problems like modeling of physical processes, wildfire, natural hazards and metal nanostructures, workforce planning, wireless network topology, parameter settings for controlling different processes, extracting elements from video clips, and management of cloud computing environment. It shows readers how to develop algorithms for these problems based on new intelligent methods like evolutionary computations, ant colony optimization, and constraint programming, and demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.

ISBN: 9783030227234$q(electronic bk.)

Standard No.: 10.1007/978-3-030-22723-4doiSubjects--Topical Terms:

252884
Mathematical optimization

LC Class. No.: QA402.5

Dewey Class. No.: 006.3

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520 $a The book presents a comprehensive collection of extended contributions from the Workshops on Computational Optimization and Numerical Search and Optimization 2018. Our everyday life is unthinkable without optimization as we try to minimize our effort while maximizing profit. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. The book discusses recent advances in computational optimization to address important real-world problems like modeling of physical processes, wildfire, natural hazards and metal nanostructures, workforce planning, wireless network topology, parameter settings for controlling different processes, extracting elements from video clips, and management of cloud computing environment. It shows readers how to develop algorithms for these problems based on new intelligent methods like evolutionary computations, ant colony optimization, and constraint programming, and demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.
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