Buch, Englisch, Band 171, 202 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 494 g
Reihe: International Series in Operations Research & Management Science
Buch, Englisch, Band 171, 202 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 494 g
Reihe: International Series in Operations Research & Management Science
ISBN: 978-1-4614-3231-9
Verlag: Springer
The above innovative approach has now evolved to the point where there are many, both theoretical and algorithmic, results that exploit the nexus between graph theoretic structures and both probabilistic and algebraic entities of related Markov chains. The latter include moments of first return times, limiting frequencies of visits to nodes, or the spectra of certain matrices traditionally associated with the analysis of Markov chains. However, these results and algorithms are dispersed over many research papers appearing in journals catering to disparate audiences. As a result, the published manuscripts are often written in a very terse manner and use disparate notation, thereby making it difficult for new researchers to make use of the many reported advances.
Hence the main purpose of this book is to present a concise and yet easily accessible synthesis of the majority of the theoretical and algorithmicresults obtained so far. In addition, the book discusses numerous open questions and problems that arise from this body of work and which are yet to be fully solved. The approach casts the Hamiltonian Cycle Problem in a mathematical framework that permits analytical concepts and techniques, not used hitherto in this context, to be brought to bear to further clarify both the underlying difficulty of NP-completeness of this problem and the relative exceptionality of truly difficult instances. Finally, the material is arranged in such a manner that the introductory chapters require very little mathematical background and discuss instances of graphs with interesting structures that motivated a lot of the research in this topic. More difficult results are introduced later and are illustrated with numerous examples.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik Mathematik Operations Research
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
Illustrative Graphs.- Intriguing Properties.- Markov Chains.- Markov Decision Processes.- Determinants.- Traces.- Linear Programming Based Algorithms.- Interior Point and Cross-Entropy Algorithms.- Self-similar Structure and Hamiltonicity.- Graph Enumeration.