By D. Du, et. al.,
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Extra resources for Handbook of combinatorial optimization Suppl. B
E. e. the largest value of On the basis of the discussion above, the pseudocode for a data correcting algorithm for SPLP is given below. It works by maintaining three sets, containing the sites where facilities are to be located, containing the sites where facilities are not to be located, and containing the rest of the sites. RO and RC rules are assumed to be able to manipulate these three sets. 4 41 Computational Experience with SPLP Instances We report our computational experience with the DCA-SPLP on several benchmark instances of the SPLP in the remainder of this section.
From Figure 9 it seems that for dense graphs, values of 3 or 4 are most favorable. This effect also holds for larger instances — Figure 10 shows the execution times for instances with and We next report the results of our experiments to solve large sized QCP instances with Using results obtained from the previous part of our study, we choose to use DCA-MSFr(3) as our algorithm of choice. We consider instances of the QCP with size ranging from 100 to 500 and densities varying between 10% and 100%.
The goal is to determine or at least to estimate the Steiner ratio for many different spaces. Banach-Minkowski Spaces 2 Obviously, Steiner’s Problem depends essentially on the way how the distances in the plane are determined. In the present paper we consider finitedimensional Banach spaces. These are defined in the following way: 2 This is a shortest tree interconnecting a finite set of points without Steiner points. D. Cieslik 58 denotes the affine space with origin o. That means; is a set of points and these points act over a linear space.
Handbook of combinatorial optimization Suppl. B by D. Du, et. al.,