288 research outputs found
Constructive characterizations of the value function of a mixed-integer program / BEBR No. 784
Bibliography: p. [44]-[45]
The simplex algorithm with the pivot rule of maximizing criterion improvement
AbstractWe extend a result of Klee and Minty by showing that the Simplex Algorithm with the pivot rule of maximizing criterion improvement is not a good algorithm in the sense of Edmonds. The method of proof extends to other similar pivot rules
An Approximation Algorithm for Stackelberg Network Pricing
We consider the problem of maximizing the revenue raised from tolls set on
the arcs of a transportation network, under the constraint that users are
assigned to toll-compatible shortest paths. We first prove that this problem is
strongly NP-hard. We then provide a polynomial time algorithm with a worst-case
precision guarantee of , where denotes the number of
toll arcs. Finally we show that the approximation is tight with respect to a
natural relaxation by constructing a family of instances for which the
relaxation gap is reached.Comment: 38 page
Nonlinear Integer Programming
Research efforts of the past fifty years have led to a development of linear
integer programming as a mature discipline of mathematical optimization. Such a
level of maturity has not been reached when one considers nonlinear systems
subject to integrality requirements for the variables. This chapter is
dedicated to this topic.
The primary goal is a study of a simple version of general nonlinear integer
problems, where all constraints are still linear. Our focus is on the
computational complexity of the problem, which varies significantly with the
type of nonlinear objective function in combination with the underlying
combinatorial structure. Numerous boundary cases of complexity emerge, which
sometimes surprisingly lead even to polynomial time algorithms.
We also cover recent successful approaches for more general classes of
problems. Though no positive theoretical efficiency results are available, nor
are they likely to ever be available, these seem to be the currently most
successful and interesting approaches for solving practical problems.
It is our belief that the study of algorithms motivated by theoretical
considerations and those motivated by our desire to solve practical instances
should and do inform one another. So it is with this viewpoint that we present
the subject, and it is in this direction that we hope to spark further
research.Comment: 57 pages. To appear in: M. J\"unger, T. Liebling, D. Naddef, G.
Nemhauser, W. Pulleyblank, G. Reinelt, G. Rinaldi, and L. Wolsey (eds.), 50
Years of Integer Programming 1958--2008: The Early Years and State-of-the-Art
Surveys, Springer-Verlag, 2009, ISBN 354068274
Linear programs and convex hulls over fields of puiseux fractions
We describe the implementation of a subfield of the field of formal Puiseux series in polymake. This is employed for solving linear programs and computing convex hulls depending on a real parameter. Moreover, this approach is also useful for computations in tropical geometry
A formally verified abstract account of Gödel's incompleteness theorems
We present an abstract development of Gödelâs incompleteness theorems, performed with the help of the Isabelle/HOL theorem prover. We analyze sufficient conditions for the theoremsâ applicability to a partially specified logic. In addition to the usual benefits of generality, our abstract perspective enables a comparison between alternative approaches from the literature. These include Rosserâs variation of the first theorem, Jeroslowâs variation of the second theorem, and the S ÌwierczkowskiâPaulson semantics-based approach. As part of our frameworkâs validation, we upgrade Paulsonâs Isabelle proof to produce a mech- anization of the second theorem that does not assume soundness in the standard model, and in fact does not rely on any notion of model or semantic interpretation
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