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  3. linear programming

Optimization for Decision Making: Linear and Quadratic Models (Repost)

Posted By: AvaxGenius
Date: 17 Aug 2022 03:56:29
Optimization for Decision Making: Linear and Quadratic Models (Repost)

Optimization for Decision Making: Linear and Quadratic Models by Katta G. Murty
English | PDF | 2010 | 502 Pages | ISBN : 1441912908 | 4.5 MB

Optimization for Decision Making: Linear and Quadratic Models is a first-year graduate level text that illustrates how to formulate real world problems using linear and quadratic models; how to use efficient algorithms – both old and new – for solving these models; and how to draw useful conclusions and derive useful planning information from the output of these algorithms. While almost all the best known books on LP are essentially mathematics books with only very simple modeling examples, this book emphasizes the intelligent modeling of real world problems, and the author presents several illustrative examples and includes many exercises from a variety of application areas.
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Foundations of Optimization (Repost)

Posted By: AvaxGenius
Date: 23 Apr 2022 06:19:08
Foundations of Optimization (Repost)

Foundations of Optimization by Osman Güler
English | PDF | 2010 | 445 Pages | ISBN : 0387344314 | 3.8 MB

The book gives a detailed and rigorous treatment of the theory of optimization (unconstrained optimization, nonlinear programming, semi-infinite programming, etc.) in finite-dimensional spaces. The fundamental results of convexity theory and the theory of duality in nonlinear programming and the theories of linear inequalities, convex polyhedra, and linear programming are covered in detail.
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Linear Programming: Mathematics, Theory and Algorithms

Posted By: AvaxGenius
Date: 23 Feb 2022 17:44:04
Linear Programming: Mathematics, Theory and Algorithms

Linear Programming: Mathematics, Theory and Algorithms by Michael J. Panik
English | PDF | 1996 | 502 Pages | ISBN : 0792337824 | 15.7 MB

Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms.
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Combinatorial, Linear, Integer and Nonlinear Optimization Apps: COLINA Grande

Posted By: AvaxGenius
Date: 17 Oct 2021 23:52:31
Combinatorial, Linear, Integer and Nonlinear Optimization Apps: COLINA Grande

Combinatorial, Linear, Integer and Nonlinear Optimization Apps: COLINA Grande by J. MacGregor Smith
English | PDF,EPUB | 2021 | 275 Pages | ISBN : 3030758001 | 225.9 MB

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).
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Optimization Theory: A Concise Introduction

Posted By: l3ivo
Date: 12 Sep 2021 09:08:05
Optimization Theory: A Concise Introduction

Jiongmin Yong, "Optimization Theory: A Concise Introduction"
English | 2018 | ISBN: 9813237643, 0000988936 | 238 pages | EPUB | 9.2 MB
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Mathematical Structures for Computer Science, Sixth Edition

Posted By: l3ivo
Date: 24 Jan 2021 08:22:58
Mathematical Structures for Computer Science, Sixth Edition

Judith L. Gersting, "Mathematical Structures for Computer Science, Sixth Edition"
English | 2006 | ISBN: 071676864X | 784 pages | DJVU | 14.67 MB
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Linear System Theory

Posted By: l3ivo
Date: 24 Dec 2020 09:00:55
Linear System Theory

Frank M. Callier, Charles A. Desoer, "Linear System Theory"
English | 1991 | ISBN: 038797573X | 523 pages | PDF | 27.1 MB
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Algorithm Engineering: Selected Results and Surveys (Repost)

Posted By: AvaxGenius
Date: 9 Aug 2020 15:55:32
Algorithm Engineering: Selected Results and Surveys (Repost)

Algorithm Engineering: Selected Results and Surveys by Lasse Kliemann
English | PDF | 2016 | 428 Pages | ISBN : 3319494864 | 10.73 MB

Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.
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