Data Correcting Approaches in Combinatorial Optimization

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Éditeur :

Springer


Collection :

SpringerBriefs in Optimization

Paru le : 2012-10-10

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Description
?????????????????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, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis  as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization  introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance  one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.?
Pages
114 pages
Collection
SpringerBriefs in Optimization
Parution
2012-10-10
Marque
Springer
EAN papier
9781461452850
EAN EPUB
9781461452867

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
5714 Ko
Prix
49,57 €