A finite element code is developed for analysis and design of three-dimensional truss and frame structures. Structures are designed for minimum weight subject to constraints on: member stresses, Euler buckling, shell buckling, joint displacements and system natural frequencies. Structures are optimized with respect to member size and strength configuration. The finite element code may be used for analysis only, or may be coupled to an optimizer of the user's choice. The displacement method is...

Topics: Mechanical engineering, Optimization, Structural optimization, Design optimization, Mast design,...

Naval Postgraduate School

36
36

Feb 1, 2021
02/21

by
Bither, Cheryl Ann; Dougherty, Julie Anne

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A modeling strategy for the validation and analysis of large-scale optimization models is defined and demonstrated. The strategy is based on nine principles of analysis and eight principles of visualization that are applied in a user controlled hierarchical structure which is customized to a particular optimization problem. For each model a set of analytic tools, such as spreadsheets and graphs, is structured to validate and verify data and analyze the model and its results. These tools can be...

Topics: Interactive optimization, Visualization, Large-scale optimization, Military optimization

Naval Postgraduate School

791
791

Jan 15, 2013
01/13

by
Madsen, Leroy E.;Vanderplaats, Garret N.

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Cover title

Topic: OPTIMIZATION.

112
112

Oct 4, 2015
10/15

by
Vanderplaats, Garret N.

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Title from cover

Topic: OPTIMIZATION.

Cover title

Topic: OPTIMIZATION.

35 ref

Topic: optimization

Title from cover

Topic: OPTIMIZATION.

157
157

Oct 9, 2015
10/15

by
Madsen, Leroy E.;Vanderplaats, Garret N.

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Cover title

Topic: OPTIMIZATION.

137
137

Oct 8, 2015
10/15

by
Rosenthal, Richard E.

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Cover title

Topic: OPTIMIZATION.

97
97

Nov 14, 2013
11/13

by
Michel X. Goemans

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De�nition 1: A matroid M = (S, I) is a �nite ground set S together with a collection of sets...

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1944

79
79

Nov 14, 2013
11/13

by
Michel X. Goemans

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This lecture is about jump systems. While they are brie�y discussed in chapter 41 of Schrijver�s book, they are not covered extensively.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1930

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124

Nov 14, 2013
11/13

by
Dan Stratila

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Consider a planar graph G = (V,E) and a set of terminal pairs R = {(si,ti): i = 1,k}. Assume G is planar, (V, E _ R) is Eulerian, and all terminals lie on the outer face of G. In this lecture, we will cover the following results.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1937

A Java tutorial was developed as a World Wide Web (WWW) site for use in capturing user behavior data. Breadth of distribution analysis was then applied to the data collected in order to characterize the usage of the user interface through the shape, connectedness, and order of traversal of each user in the sample. The results reveal distinct user groups with different levels of user knowledge and needs in relation to the web site content The resulting user interface analysis process produces a...

Topics: OPTIMIZATION, optimization, distribution, user interface analysis

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104

Nov 14, 2013
11/13

by
Michel X. Goemans

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Today we will brie�y survey matroid representation and then discuss some problems in matroid optimization and the corresponding applications. The tools we develop will help us answer the following puzzle: Puzzle: A game is played on a graph G(V, E) and has two players, George and Ari. Ari�s moves consist of ��xing� edges e _ E. George�s moves consist of deleting any un�xed edge. The game ends when every edge has been either �xed or deleted. Ari wins if the graph at the end of...

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1923

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80

Nov 14, 2013
11/13

by
Mohammad Mahdian

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The Lovasz splitting-o_ lemma - Lovasz�s splitting-o_ lemma states the following.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1935

105
105

Nov 14, 2013
11/13

by
Michel X. Goemans

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In this lecture, we will introduce three related topics: graph orientations, directed cuts, and submodular �ows. In fact, we will use submodular �ows to prove results from the other topics.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1931

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103

Nov 14, 2013
11/13

by
Michel X. Goemans

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Last time, we saw that the matching polytope was de�ned by: ...

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1941

88
88

Nov 14, 2013
11/13

by
Michel X. Goemans

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In this lecture, we will be concerned with graph coverings by a collection of paths or cycles. The goal will be to cover all the vertices by a small number of either paths or cycles, and this number will be bounded by the independence number _(G). (_(G) is the maximum size of an independent, or stable, set, i.e. a set of vertices inducing no edges.) For a directed graph D, _(D) refers to the corresponding undirected graph. Let�s start with the following statement, proved by Gallai and Milgram...

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1942

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86

Nov 14, 2013
11/13

by
Michel X. Goemans

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In this lecture, we continue with more results on matroid union, as well as tie together some loose ends from the past couple of lectures.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1927

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3.0

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318 pages : 24 cm

Topics: Mathematical optimization, Multidisciplinary design optimization, Optimierung

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81

Nov 14, 2013
11/13

by
Michel X. Goemans

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The Matroid matching Problem: Given a matroid M = (S, I), let E be a set of pairs on S.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1929

100
100

Nov 14, 2013
11/13

by
Michel X. Goemans

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We continue the discussion of how a 2k-edge-connected graph can be oriented so that the resulting digraph is k-arc-connected. Last time we have seen that this can be achieved using submodular �ows. Today we present a di_erent approach, which relates the problem to matroid intersection.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1934

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106

Nov 14, 2013
11/13

by
Michel X. Goemans

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Let M1 = (S, I1), M2 = (S, I2) be two matroids on common ground set S with rank functions r1 and r2. Many combinatorial optimization problems can be reformulated as the problem of �nding the maximum size common independent set ..

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1924

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79

Nov 14, 2013
11/13

by
Alantha Newman

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1 Multi�ows and Disjoint Paths - Let G = (V,E) be a graph and let...

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1936

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88

Nov 14, 2013
11/13

by
Michel X. Goemans

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In this lecture, we will: � Present Edmonds� algorithm for computing a maximum matching in a (not necessarily bipartite) graph G. � Use the analysis of the algorithm to derive the Edmonds-Gallai Decomposition Theorem stated in the last lecture.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1933

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95

Nov 14, 2013
11/13

by
Michel X. Goemans

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In this lecture, we investigate the relationship between total dual integrality and integrality of polytopes. We then use a theorem on total dual integrality to provide a new proof of the Tutte-Berge formula.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1940

6
6.0

Jun 14, 2022
06/22

by
Papadimitriou, Christos H

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xvi, 496 p. : 24 cm

Topics: Mathematical optimization, Combinatorial optimization, Computational complexity

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87

Nov 14, 2013
11/13

by
Michel X. Goemans

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Our �rst topic of study is matchings in graphs which are not necessarily bipartite. We begin with some relevant terminology and de�nitions.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1922

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109

Nov 14, 2013
11/13

by
Michel X. Goemans

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This lecture covers the proof of the Bessy-Thomasse Theorem, formerly known as the Gallai Conjecture. Also, we discuss the cyclic stable set polytope, and show that it is totally dual integral (TDI) (see lecture 5 for more on TDI systems of inequalities).

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1943

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90

Nov 14, 2013
11/13

by
Michel X. Goemans

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Last time, we stated the following theorem by Edmonds and Lawler about the maximum independent set common to two matroids.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1925

4
4.0

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xxi, 546 p. : 25 cm

Topics: Mathematical optimization, Mathematical optimization -- Case studies

285
285

May 30, 2010
05/10

by
Novoselov, V. S

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Analytical dynamic methods applied to flight optimization

Topics: DYNAMICS, FLIGHT OPTIMIZATION, DYNAMICS, FLIGHT OPTIMIZATION

115
115

Nov 14, 2013
11/13

by
Michel X. Goemans

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This lecture covers: the Matching polytope, total dual integrality, and Hilbert bases.

Topics: Maths, Optimization and Control, Optimization, Mathematics

Source: http://www.flooved.com/reader/1939

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110

Nov 14, 2013
11/13

by
Santosh Vempala

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A linear program consists of linear constraints with the goal of maximizing or minimizing a linear objective function subject to the constraints

Topics: Maths, Optimization and Control, Control and Optimization, Optimization, Linear Programming,...

Source: http://www.flooved.com/reader/1312

Optimization problems are the most interesting problems to discuss in mathematics. Optimization is used to modeling problems in various field to achieve the effectiveness and efficiency of the desired target. One of the optimization problems that are often encountered in everyday life is the selection and packaging of items with limited media or knapsack to get maximum profit. This problem is well-known as knapsack problem. There are various types of knapsack problems, one of them is quadratic...

Topics: Knapsack, Optimization, Quadratic Bounded Knapsack, Particle Swarm Optimization, Golden Eagle...

6
6.0

Mar 9, 2022
03/22

by
Haftka, Raphael T

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xiv, 396 p. : 25 cm

Topic: Structural optimization

Naval Postgraduate School

200
200

Jan 14, 2013
01/13

by
Adamec, David;Elsberry, Russell L;Garwood, Roland W;Haney, Robert Lee

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"NPS63-80-003"--Cover

Topic: COMBINATORIAL OPTIMIZATION

6
6.0

Mar 26, 2021
03/21

by
Tang, S. L. (Siu-lam)

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vi, 160 p. : 25 cm

Topic: Mathematical optimization

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40

Jun 1, 2022
06/22

by
Fletcher, R. (Roger)

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v. : 24 cm

Topic: Mathematical optimization

280
280

Feb 26, 2019
02/19

by
Boyd

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Convex optimization book

Topic: convex optimization

3
3.0

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ix, 384 p. : 24 cm

Topic: Combinatorial optimization

This dissertation investigates Multidimensional Packing Problems (MD-PPs): the Pallet Loading Problem (PLP), the Multidimensional Knapsack Problem (MD-KP), and the Multidimensional Bin Packing Problem (MD-BPP). In these problems, there is a set of items, with rectangular dimensions, and a set of large containers, or bins, also with rectangular dimensions. Items cannot overlap (share the same region in space), and, when packed, must be completely located within the bin. We develop new theory for...

Topic: Combinatorial optimization

10
10.0

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186 p. : 24 cm

Topic: Combinatorial optimization

31 l. 28 cm

Topic: Mathematical optimization

8
8.0

Jan 25, 2022
01/22

by
Clarke, Frank H

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xii, 308 p. : 23 cm

Topic: Nonsmooth optimization

202
202

Jul 18, 2014
07/14

by
Wilde, Douglass J

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Bibliographical footnotes

Topic: Mathematical optimization

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32

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xii, 253 p. : 26 cm. --

Topic: Mathematical optimization

1,187
1.2K

Sep 4, 2008
09/08

by
Naert, Philippe, A

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Bibliography: leaves 45-46

Topic: Mathematical optimization

1,492
1.5K

Aug 12, 2018
08/18

by
Stephen Boyd

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Catalog description Concentrates on recognizing and solving convex optimization problems that arise in applications. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods. Applications to signal processing, statistics and machine learning, control and...

Topics: Optimization, Math

Source: http://academictorrents.com/details/393dc896234b96a1cd251c14cfc65d2ff594d6e9

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15

May 11, 2021
05/21

by
Panik, Michael J

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xi, 312 p. ; 24 cm

Topic: Mathematical optimization