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Titlebook: Combinatorial, Linear, Integer and Nonlinear Optimization Apps; COLINA Grande J. MacGregor Smith Textbook 2021 Springer Nature Switzerland

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发表于 2025-3-21 19:41:49 | 显示全部楼层 |阅读模式
书目名称Combinatorial, Linear, Integer and Nonlinear Optimization Apps
副标题COLINA Grande
编辑J. MacGregor Smith
视频video
概述Conceptually explains real world optimization problems which are then demonstrated with practical software apps.Brings optimization down to the students’ personal lives and experiences and gives them
丛书名称Springer Optimization and Its Applications
图书封面Titlebook: Combinatorial, Linear, Integer and Nonlinear Optimization Apps; COLINA Grande J. MacGregor Smith Textbook 2021 Springer Nature Switzerland
描述.This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN). Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and relatedmathematics..
出版日期Textbook 2021
关键词combinatorial optimization; integer; linear; nonlinear; programming apps; smart phones; tablets; textbook o
版次1
doihttps://doi.org/10.1007/978-3-030-75801-1
isbn_softcover978-3-030-75803-5
isbn_ebook978-3-030-75801-1Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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发表于 2025-3-22 00:19:44 | 显示全部楼层
J. MacGregor SmithConceptually explains real world optimization problems which are then demonstrated with practical software apps.Brings optimization down to the students’ personal lives and experiences and gives them
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App Problem Formulation,In this chapter, we give the reader an overview of problem formulation and its relationship to App development and how Operations Research and Computer Science strategies are helpful in constructing methodologies for their solution. See Figure below.
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Shahriar Mahmud,Shakti Raj Chopraex to solve because of the nonlinear, non-convex effects of the integer decision variables. Most of the IP problems for large scale instances are at least . Complete for the decision problem, and many are . Hard for the optimization part, so that getting optimal solutions is often out of the questio
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https://doi.org/10.1007/978-981-19-7198-3 dominated the literature in Operations Research. This is because some of the nice properties such as monotonicity and convexity in Linear Programming are not always possible with NLP problems, so many local optimal solutions will exist, not just a single global optimization one. Figure . illustrate
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