103 research outputs found
Using SVGāXML FOR representation of historical graphical data
Modern data representation requires XML-based approach. One of the ways to
represent any kind of graphical data in electronic form is to use Scalable
Vector Graphics (SVG). So, XML and SVG are ideal means for the digital
representation of national heritage. Moreover, for the powerful using of SVG
one should learn a very complex syntax and related XML applications. In this
paper the advantages and drawbacks of SVG, in processing of national
heritage, are specified. Some examples about processing frescos and
manuscripts are presented
A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem
In this paper the low autocorrelation binary sequence problem (LABSP) is modeled as a mixed integer quadratic programming (MIQP)
problem and proof of the modelās validity is given. Since the MIQP model is semidefinite, general optimization solvers can be used, and converge in a finite number of iterations. The experimental results show that IQP solvers, based on this MIQP formulation, are capable of optimally solving general/skew-symmetric LABSP instances of up to 30/51 elements in a moderate time. ACM Computing Classification System (1998): G.1.6, I.2.8.This research was partially supported by the Serbian Ministry of Education and Science
under projects 174010 and 174033
An electromagnetism-like method for the maximum set splitting problem
In this paper, an electromagnetism-like approach (EM) for solving the maximum set splitting problem (MSSP) is applied. Hybrid approach consisting of the movement based on the attraction-repulsion mechanisms combined with the proposed scaling technique directs EM to promising search regions. Fast implementation of the local search procedure additionally improves the efficiency of overall EM system. The performance of the proposed EM approach is evaluated on two classes of instances from the literature: minimum hitting set and Steiner triple systems. The results show, except in one case, that EM reaches optimal solutions up to 500 elements and 50000 subsets on minimum hitting set instances. It also reaches all optimal/best-known solutions for Steiner triple systems
Solving the Task Assignment Problem with a Variable Neighborhood Search
In this paper a variable neighborhood search (VNS) approach
for the task assignment problem (TAP) is considered. An appropriate neighborhood
scheme along with a shaking operator and local search procedure
are constructed specifically for this problem. The computational results are
presented for the instances from the literature, and compared to optimal
solutions obtained by the CPLEX solver and heuristic solutions generated
by the genetic algorithm. It can be seen that the proposed VNS approach
reaches all optimal solutions in a quite short amount of computational time.* This research was partially supported by the Serbian Ministry of Science and Ecology under
project 144007
A new lower bound for doubly metric dimension and related extremal differences
In this paper a new graph invariant based on the minimal hitting set problem
is introduced. It is shown that it represents a tight lower bound for the
doubly metric dimension of a graph. Exact values of new invariant for paths,
stars, complete graphs and complete bipartite graph are obtained. The paper
analyzes some tight bounds for the new invariant in general case. Also several
extremal differences between some related invariants are determined
An Electromagnetism-Like Approach for Solving the Low Autocorrelation Binary Sequence Problem
In this paper an electromagnetism-like approach (EM) for solving the low autocorrelation binary sequence problem (LABSP) is applied. This problem is a notoriously difficult computational problem and represents a major challenge to all search algorithms. Although EM has been applied to the topic of optimization in continuous space and a small number of studies on discrete problems, it has potential for solving this type of problems, since movement based on the attraction-repulsion mechanisms combined with the proposed scaling technique directs EM to promising search regions. Fast implementation of the local search procedure additionally improves the efficiency of the overall EM system
Solving the Maximally Balanced Connected Partition Problem in Graphs by Using Genetic Algorithm
This paper exposes a research of the NP-hard Maximally Balanced Connected Partition problem (MBCP). The proposed solution comprises of a genetic algorithm (GA) that uses: binary representation, fine-grained tournament selection, one-point crossover, simple mutation with frozen genes and caching technique. In cases of unconnected partitions, penalty functions are successfully applied in order to obtain the feasible individuals. The effectiveness of presented approach is demonstrated on the grid graph instances and on random instances with up to 300 vertices and 2 000 edges
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