K Bérczi, Y Kobayashi - Journal of Combinatorial Theory, Series B, 2012 - Elsevier
We consider the problem of making a given (k− 1)-connected graph k-connected by adding a minimum number of new edges, which we call the k-connectivity augmentation problem. In …
K Murota - Optimization Methods and Software, 2021 - Taylor & Francis
Discrete convex functions are used in many areas, including operations research, discrete- event systems, game theory, and economics. The objective of this paper is to investigate …
Y Kobayashi - Discrete Optimization, 2010 - Elsevier
In this paper, we consider the problem of finding a maximum weight 2-matching containing no cycle of a length of at most three in a weighted simple graph, which we call the weighted …
K Takazawa - Discrete Optimization, 2017 - Elsevier
We introduce a new framework for restricted 2-matchings close to Hamilton cycles. For an undirected graph (V, E) and a family U of vertex subsets, a 2-matching F is called U-feasible …
K Takazawa - Discrete Applied Mathematics, 2017 - Elsevier
AC k-free 2-matching in an undirected graph is a simple 2-matching which does not contain cycles of length k or less. The complexity of finding the maximum C k-free 2-matching in a …
The problem of finding a maximum $2 $-matching without short cycles has received significant attention due to its relevance to the Hamilton cycle problem. This problem is …
K Takazawa - … : 19th International Conference, IPCO 2017, Waterloo …, 2017 - Springer
We propose a new framework of optimal t-matchings excluding prescribed t-factors in bipartite graphs. It is a generalization of the nonbipartite matching problem and includes a …
D Hartvigsen - Journal of Graph Theory, 2024 - Wiley Online Library
A 2‐factor in a graph GG is a subset of edges MM such that every node of GG is incident with exactly two edges of M M. Many results are known concerning 2‐factors including a …
N Minamikawa, A Shioura - … of the Operations Research Society of …, 2021 - jstage.jst.go.jp
The concept of M-convex function gives a unified framework for discrete optimization problems with nonlinear objective functions such as the minimum convex cost flow problem …