Linear Programming and Network Flows

By M. Bazaraa, J. J. Jarvis, Hanif D. Sherali. 1977

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Citations in the corpus

Planning in the Presence of Cost Functions Controlled by an Adversary (2003, methodology): “We focus on the application of this technique to the problem at hand, and refer the reader to other sources for a more general introduction (Bazaraa et al., 1990).”
Ones Assignment Method for Solving Assignment Problems (2012, background): “april 22nd, 2018 - note after row and column scanning if you stuck with more than one zero in the matrix please do the row scanning and column scanning repeatedly as much' 'Synthesis of Research on Problem Solving April 28th, 2018 - Mathematics teachers talk about 2 / 13 write about and act upon…”
Predictive Control for Linear and Hybrid Systems (2017, unknown): “the Klee-Minty cube which is a polyhedral set in R with 2 vertices [26].”
Hybrid Taguchi-genetic algorithm for global numerical optimization (2004, methodology): “If the th gene of the vector is often chosen to execute the convex combination [2], [7], the precision of the value of the th gene can be extended in the exploration process.”
Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model (2014, background): “, , ), the proposed protection functions of (20) and (21) can be recast into minimization problems by applying duality theory [36] as given in [20]:”
Robust Optimization of Experimentally Derived Objective Functions (2003, background): “Since f (x, b) is linear in b and g(b) is concave in b, f (x, b) − g(b) is convex in b. Maximization of a convex function is achieved at the extreme point of the feasible region; see Bazaraa et al. (1990).”
Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach (2009, background): “Note that based on the fundamental theorem of duality ( Bazaraa et al. 2005 ), one of the followings is true”
The linear separability problem: some testing methods (2006, background): “Two of the most popular ones are the Fourier‐Kuhn elimination and the Simplex Method [7]‐[ 10 ].”
DASSO: connections between the Dantzig selector and lasso (2009, background): “ard linear programming arguments; for example see page 298 of Bazaraa et al. (1990). The last column of B can be assigned in such a way that, if we define xB.”
Linear and Nonlinear Optimization (2008, background): “as the null-space matrix for A, the reduced gradient would be ẐT∇f (x̄) = Ẑ(8, 2, 0) = (18, 8), www.”