Disjoint Chorded Cycles in Graphs with High Ore-Degree
In 1963, Corrádi and Hajnal proved that for all k ≥ 1, every graph with at least 3k vertices and minimum degree at least 2k has k vertex-disjoint chorded cycles. In 2010, Chiba, Fujita, Gao, and Li proved that for all k ≥ 1, every graph with |G|≥ 4k and m
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Andrei M. Raigorodskii Michael Th. Rassias Editors
Discrete Mathematics and Applications
Springer Optimization and Its Applications Volume 165 Series Editors Panos M. Pardalos , University of Florida My T. Thai , University of Florida Honorary Editor Ding-Zhu Du, University of Texas at Dallas Advisory Editors Roman V. Belavkin, Middlesex University John R. Birge, University of Chicago Sergiy Butenko, Texas A&M University Vipin Kumar, University of Minnesota Anna Nagurney, University of Massachusetts Amherst Jun Pei, Hefei University of Technology Oleg Prokopyev, University of Pittsburgh Steffen Rebennack, Karlsruhe Institute of Technology Mauricio Resende, Amazon Tamás Terlaky, Lehigh University Van Vu, Yale University Michael N. Vrahatis, University of Patras Guoliang Xue, Arizona State University Yinyu Ye, Stanford University
Aims and Scope Optimization has continued to expand in all directions at an astonishing rate. New algorithmic and theoretical techniques are continually developing and the diffusion into other disciplines is proceeding at a rapid pace, with a spot light on machine learning, artificial intelligence, and quantum computing. Our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in areas not limited to applied mathematics, engineering, medicine, economics, computer science, operations research, and other sciences. The series Springer Optimization and Its Applications (SOIA) aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks, handbooks) that focus on theory, methods, and applications of optimization. Topics covered include, but are not limited to, nonlinear optimization, combinatorial optimization, continuous optimization, stochastic optimization, Bayesian optimization, optimal control, discrete optimization, multi-objective optimization, and more. New to the series portfolio include Works at the intersection of optimization and machine learning, artificial intelligence, and quantum computing. Volumes from this series are indexed by Web of Science, zbMATH, Mathematical Reviews, and SCOPUS.
More information about this series at http://www.springer.com/series/7393
Andrei M. Raigorodskii • Michael Th. Rassias Editors
Discrete Mathematics and Applications
Editors Andrei M. Raigorodskii Moscow Institute of Physics and Technology Dolgoprudny, Russia Moscow State University Moscow, Russia Buryat State University Ulan-Ude, Russia Caucasus Mathematical Center Adyghe State University Maykop, Russia
Michael Th. Rassias Institute of Mathematics University of Zurich Zurich, Switzerland Moscow Institute of Physics and Technology Dolgoprudny, Russia Institute for Advanced Study Program in Interdisciplinary Studies Princeton, NJ, USA
ISSN 1931-6828 ISSN 1931-6836 (electronic) Springer Optimization and Its Applications ISBN 978-3-030-55856-7 ISBN 978-3-030-558
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