Data Correcting Approaches in Combinatorial Optimization
Series: SpringerBriefs in Optimization
Goldengorin, Boris, Pardalos, Panos M.
2012, 2012, X, 114 p. 41 illus.
Softcover
Information
ISBN 978-1-4614-5285-0
(net)
49,95 €
About this book
Data Correcting Approaches in Combinatorial Optimization focuses
on algorithmic applications of the well known polynomially solvable
special cases of computationally intractable problems. The purpose
of this text is to design practically efficient algorithms for
solving wide classes of combinatorial optimization problems.
Researches, students and engineers will benefit from new bounds
and branching rules in development efficient branch-and-bound type
computational algorithms. This book examines applications for
solving the Traveling Salesman Problem and its variations, Quadratic
Cost Partition and Its Special Case: Max-Cut Problem, Different
Classes of Allocation and Cluster Analysis as well as some classes
of Scheduling Problems.
Extensive computational experiments with Data Correcting Algorithms
show that, for example, the so called multilevel Data Correcting
Algorithm (DCA) for submodular function applied to the Quadratic
Cost Partition Problem is able to solve its benchmark instances
defined on dense graphs with up to 500 vertices within 10 min on a
standard PC. A single level DCA is included in MATLAB Toolbox for
submodular function optimization and maintained by Andreas Krause.
Content Level » Research
Keywords » algorithmics - cluster analysis - combinatorial
optimization - data correcting
Related subjects » Computational Science & Engineering - Mathematics -
Theoretical Computer Science
http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-1-4614-5285-0
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