Displaying similar documents to “ Δ -matroid and jump system.”

A nonsmooth version of the univariate optimization algorithm for locating the nearest extremum (locating extremum in nonsmooth univariate optimization)

Marek Smietanski (2008)

Open Mathematics

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An algorithm for univariate optimization using a linear lower bounding function is extended to a nonsmooth case by using the generalized gradient instead of the derivative. A convergence theorem is proved under the condition of semismoothness. This approach gives a globally superlinear convergence of algorithm, which is a generalized Newton-type method.

Inequality-sum : a global constraint capturing the objective function

Jean-Charles Régin, Michel Rueher (2005)

RAIRO - Operations Research - Recherche Opérationnelle

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This paper introduces a new method to prune the domains of the variables in constrained optimization problems where the objective function is defined by a sum y = Σ x i , and where the integer variables x i are subject to difference constraints of the form x j - x i c . An important application area where such problems occur is deterministic scheduling with the mean flow time as optimality criteria. This new constraint is also more general than a sum constraint defined on a set of ordered variables. Classical...

Extensions of linear operators from hyperplanes of l ( n )

Marco Baronti, Vito Fragnelli, Grzegorz Lewicki (1995)

Commentationes Mathematicae Universitatis Carolinae

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Let Y l ( n ) be a hyperplane and let A ( Y ) be given. Denote 𝒜 = { L ( l ( n ) , Y ) : L Y = A } and λ A = inf { L : L 𝒜 } . In this paper the problem of calculating of the constant λ A is studied. We present a complete characterization of those A ( Y ) for which λ A = A . Next we consider the case λ A > A . Finally some computer examples will be presented.

A Distance-Based Method for Attribute Reduction in Incomplete Decision Systems

Demetrovics, Janos, Thi, Vu Duc, Giang, Nguyen Long (2013)

Serdica Journal of Computing

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There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods.