Titlebook: Integer Programming and Combinatorial Optimization; 16th International C Michel Goemans,José Correa Conference proceedings 2013 Springer-Ve

座右铭

,Reverse Chvátal-Gomory Rank,is .. A well-known example in dimension two shows that there exist integral polytopes . with ..(.) = + ∞. We provide a geometric characterization of polyhedra with this property in general dimension, and investigate upper bounds on ..(.) when this value is finite. We also sketch possible extensions,

languor

On Some Generalizations of the Split Closure,e of a rational polyhedron . is again a polyhedron. In this paper, we extend this result from a single rational polyhedron to the union of a finite number of rational polyhedra. We also show how this result can be used to prove that some generalizations of split cuts, namely cross cuts, also yield c

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Packing Interdiction and Partial Covering Problems,is to harm the LP: which variables should we forbid the LP from using (subject to forbidding variables of total interdiction cost at most the budget) in order to minimize the value of the resulting LP? Interdiction problems on graphs (interdicting the maximum flow, the shortest path, the minimum spa

奴才

On Valid Inequalities for Quadratic Programming with Continuous Variables and Binary Indicators,ry indicators on whether or not . > 0. This structure appears when deriving strong relaxations for mixed integer quadratic programs (MIQPs). Valid inequalities for this set can be obtained by lifting inequalities for a related set without binary variables (.), that was studied by Burer and Letchford

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玉米棒子

Single Commodity-Flow Algorithms for Lifts of Graphic and Co-graphic Matroids,ime we can either solve the single commodity flow problem for . or find an obstruction for which the Max-Flow Min-Cut relation does not hold. The key tool is an algorithmic version of Lehman’s Theorem for the set covering polyhedron.

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A Stochastic Probing Problem with Applications,.:. ∈ .} and the goal is to maximize the weight of a chosen subset . of active elements. However, we are given only the .. values—to determine whether or not an element . is active, our algorithm must . .. If element . is probed and happens to be active, then . must irrevocably be added to the chose

ALE

Thrifty Algorithms for Multistage Robust Optimization,e cost of taking actions increases. The dilemma for the decision-maker is whether to wait for additional information and risk the inflation, or to take early actions to hedge against rising costs. We study the “.-robust” uncertainty model: in each stage . = 0, 1, …, ., the algorithm is shown some su

GEAR

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