Download Integer Programming and Combinatorial Optimization: 12th by Kent Andersen, Quentin Louveaux, Robert Weismantel, Laurence PDF
By Kent Andersen, Quentin Louveaux, Robert Weismantel, Laurence A. Wolsey (auth.), Matteo Fischetti, David P. Williamson (eds.)
This e-book constitutes the refereed lawsuits of the twelfth overseas convention on Integer Programming and Combinatorial Optimization, IPCO 2007, held in Ithaca, manhattan, united states, in June 2007.
The 36 revised complete papers provided have been rigorously reviewed and chosen from over a hundred and twenty submissions. one of the themes addressed are approximation algorithms, algorithmic online game idea, department and certain algorithms, department and minimize algorithms, computational biology, computational complexity, computational geometry, slicing airplane algorithms, diophantine equations, geometry of numbers, graph and community algorithms, integer programming, matroids and submodular services, online algorithms and aggressive research, polyhedral combinatorics, randomized algorithms, random graphs, scheduling idea and scheduling algorithms, in addition to semidefinite programs.
Read or Download Integer Programming and Combinatorial Optimization: 12th International IPCO Conference, Ithaca, NY, USA, June 25-27, 2007. Proceedings PDF
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Extra info for Integer Programming and Combinatorial Optimization: 12th International IPCO Conference, Ithaca, NY, USA, June 25-27, 2007. Proceedings
Sample text
Their algorithm is similar in style to the one presented in this paper: it is primal-dual (as in [9]) and provides a proof of the polyhedral result. Finally, we note that there is a fairly extensive literature involving the study of matching problems in regular graphs, particularly in cubic graphs. Here are some of the highlights: • Kaiser and Skrekovski [20] showed that every bridgeless cubic graph has a 2-factor that intersects all edge cuts of size 3 or 4. This result implies that every bridgeless cubic graph has a C3 -free 2-factor.
27] H. D. Sherali and C. H. Tun¸cbilek. A hierarchy of relaxations between continuous and convex hull representations for zero-one programming problems. SIAM Journal on Discrete Mathematics, 3:411–430, 1990. [28] H. D. Sherali and C. H. Tun¸cbilek. A reformulation-convexification approach for solving nonconvex quadratic programming problems. Journal of Global Optimization, 7:1–31, 1995. [29] R. Stubbs and S. Mehrotra. A branch-and-cut methods for 0-1 mixed convex programming. Mathematical Programming, 86:515–532, 1999.
Richard To illustrate the idea that motivates this definition, we discuss the case where n m = 1. Consider a row of the simplex tableau i=1 ai xi = a0 of an integer program, where ai ∈ R, the fractional part of a0 is r = 0, and xi are nonnegative integer variables. If φ is a valid function for P I(r, 1) we have that ni=1 φ(ai )xi ≥ 1 is a valid cut for the original IP. Multiplying this cut with r and then subtracting n it from the original row we obtain i=1 [φ]r (ai )xi ≤ [φ]r (a0 ). One well-known example of the relation between the group-space and the lifting-space representation of an inequality is that of Gomory Mixed Integer Cut (GMIC) and the Mixed Integer Rounding (MIR) inequality.