Masashi Kiyomi

FIXED-FLOOD-IT and FREE-FLOOD-IT are combinatorial problems on graphs that generalize a very popular puzzle called Flood-It. Both problems consist of recoloring moves whose goal is to produce a monochromatic ("flooded") graph as quickly as possible. Their difference is that in FREE-FLOOD-IT the player has the additional freedom of choosing the vertex to play in each move. In this paper, we investigate how this freedom affects the complexity of the problem. It turns out that the freedom is bad in some sense. We show that some cases trivially solvable for FIXED-FLOOD-IT become intractable for FREE-FLOOD-IT. We also show that some tractable cases for FIXED-FLOOD-IT are still tractable for FREE-FLOOD-IT but need considerably more involved arguments. We finally present some combinatorial properties connecting or separating the two problems. In particular, we show that the length of an optimal solution for FIXED-FLOOD-IT is always at most twice that of FREE-FLOOD-IT, and this is tight.

In this paper, a general framework for enumerating every element in a graph class is given. The main feature of this framework is that it is designed to enumerate only non-isomorphic graphs in a graph class. Applying this framework to the classes of interval graphs and permutation graphs, we give efficient enumeration algorithms for these graph classes such that each element in the class is output in a polynomial time delay. The experimental results are also provided. The catalogs of graphs in these graph classes are also provided.

An alliance in a graph is a set of vertices that is either safe under attacks from the neighborhood (defensive), capable of attacking its neighbors (offensive), or simultaneously defensive and offensive (powerful). An alliance is global if all nonmembers are adjacent to some members of the alliance. The concept of alliances was introduced by Kristiansen et al. (2004). After that many results concerning the complexity for finding a minimum alliance were shown. It was shown that the problem of finding a minimum alliance of any variant is NP-hard in general. For some variants, it was shown that the problem becomes polynomial time solvable when restricted to trees or series-parallel graphs. In this paper, we show that the problems for all variants are efficiently solvable for much larger graph classes. We present a polynomial-time algorithm for graphs of bounded clique-width. We also show that the problem is fixed-parameter tractable when parameterized by the vertex cover number. (C) 2017 Elsevier B.V. All rights reserved.

We present a polynomial-time algorithm for solving SUBGRAPH ISOMORPHISM where the base graphs are bipartite permutation graphs and the pattern graphs are chain graphs. (C) 2016 Elsevier B.V. All rights reserved.

Many graph parameters of grid-like graphs are studied because of their algorithmic consequences. An important concept in this context is that of treewidth. Treewidth of graphs is a graph parameter for measuring how close a graph is to a tree. In this paper, we study the treewidth of toroidal grids and show that the treewidth of the n x n toroidal grid is either 2n - 2 or 2n - 1. We then show that these bounds are tight in some cases. To show the lower bounds, we construct brambles of high orders. (C) 2015 Elsevier B.V. All rights reserved.

Consider a puzzle consisting of n tokens on an n-vertex graph, where each token has a distinct starting vertex and a distinct target vertex it wants to reach, and the only allowed transformation is to swap the tokens on adjacent vertices. We prove that every such puzzle is solvable in O(n(2)) token swaps, and thus focus on the problem of minimizing the number of token swaps to reach the target token placement. We give a polynomial-time 2-approximation algorithm for trees, and using this, obtain a polynomial-time 2 alpha-approximation algorithm for graphs whose tree a-spanners can be computed in polynomial time. Finally, we show that the problem can be solved exactly in polynomial time on complete bipartite graphs. (C) 2015 Elsevier B.V. All rights reserved.

We provide algorithms performing Depth-First Search (DFS) on a directed or undirected graph with n vertices and m edges using only O(n) bits. One algorithm uses O(n) bits and runs in O(mlog n) time. Another algorithm uses n+ o(n) bits and runs in polynomial time. Furthermore, we show that DFS on a directed acyclic graph can be done in space n/2(Omega(root log n)) and in polynomial time, and we also give a simple linear-time O(log n)-space algorithm for the depth-first traversal of an undirected tree. Finally, we also show that for a graph having an O(1)-size feedback set, DFS can be done in O(log n) space. Our algorithms are based on the analysis of properties of DFS and applications of the s-t connectivity algorithms due to Reingold and Barnes et al., both of which run in sublinear space.

Consider a puzzle consisting of n tokens on an n-vertex graph, where each token has a distinct starting vertex and a distinct target vertex it wants to reach, and the only allowed transformation is to swap the tokens on adjacent vertices. We prove that every such puzzle is solvable in O(n(2)) token swaps, and thus focus on the problem of minimizing the number of token swaps to reach the target token placement. We give a polynomial-time 2-approximation algorithm for trees, and using this, obtain a polynomial-time 2 alpha-approximation algorithm for graphs whose tree a-spanners can be computed in polynomial time. Finally, we show that the problem can be solved exactly in polynomial time on complete bipartite graphs.

We study a combinatorial game named "sankaku-tori" in Japanese, which means "triangle-taking" in English. It is an old pencil-and-paper game for two players played in Western Japan. The game is played on points on the plane in general position. In each turn, a player adds a line segment to join two points, and the game ends when a triangulation of the point set is completed. The player who completes more triangles than the other wins. In this paper, we consider two restricted variants of this game. In the first variant, the first player always wins in a nontrivial way, and the second variant is NP-complete in general.

PREMAGE CONSTRUCTION problem by Kratsch and Hemaspaandra naturally arose from the famous graph reconstruction conjecture. It deals with the algorithmic aspects of the conjecture. We present an O(n(8)) time algorithm for PREIMAGE CONSTRUCTION on permutation graphs and an O(n(4)(n + m)) time algorithm for PREIMAGE CONSTRUCTION on distance-hereditary graphs, where n is the number of graphs in the input, and m is the number of edges in a preimage: Since each graph of the input has n - 1 vertices and O(n(2)) edges, the input size is O(n(3)) (, or O(nm)). There are polynomial time isomorphism algorithms for permutation graphs and distance-hereditary graphs. However the number of permutation (distance-hereditary) graphs obtained by adding a vertex to a permutation (distance-hereditary) graph is generally exponentially large. Thus exhaustive checking of these graphs does not achieve any polynomial time algorithm. Therefore reducing the number of preimage candidates is the key point.

We study a character-based phylogeny reconstruction problem when an incomplete set of data is given. More specifically, we consider the situation under the directed perfect phylogeny assumption with binary characters in which for some species the states of some characters are missing. Our main object is to give an efficient algorithm to enumerate (or list) all perfect phylogenies that can be obtained when the missing entries are completed. While a simple branch-and-bound algorithm (B&amp B) shows a theoretically good performance, we propose another approach based on a zero-suppressed binary decision diagram (ZDD). Experimental results on randomly generated data exhibit that the ZDD approach outperforms B&amp B. We also prove that counting the number of phylogenetic trees consistent with a given data is #P-complete, thus providing an evidence that an efficient random sampling seems hard. © 2012 Springer-Verlag.

The Voronoi game is a two-person perfect information game modeling a competitive facility location. The original version of the game is played on a continuous domain. Only two special cases (1-dimensional case and I-round case) have been extensively investigated. Recently, the discrete Voronoi game of which the game arena is given as a graph was introduced. In this note, we give a complete analysis of the discrete Voronoi game on a path. There are drawing strategies for both the first and the second players, except for some trivial cases.

How do we most quickly fold a paper strip (modeled as a line) to obtain a desired mountain-valley pattern of equidistant creases (viewed as a binary string)? Define the folding complexity of a mountain-valley string as the minimum number of simple folds required to construct it. We first show that the folding complexity of a length-n uniform string (all mountains or all valleys), and hence of a length-n pleat (alternating mountain/valley), is O(lg(2) n). We also show that a lower bound of the complexity of the problems is Omega(lg(2) n/lg lg n). Next we show that almost all mountain-valley patterns require Omega(n/lg n) folds, which means that the uniform and pleat foldings are relatively easy problems. We also give a general algorithm for folding an arbitrary sequence of length n in O(n/lg n) folds, meeting the lower bound up to a constant factor.

The graph reconstruction conjecture is a long-standing open problem in graph theory. There are many algorithmic studies related to it, such as DECK CHECKING, LEGITIMATE DECK, PREIMAGE CONSTRUCTION, and PREIMAGE COUNTING. We study these algorithmic problems by limiting the graph class to interval graphs. Since we can solve GRAPH ISOMORPHISM for interval graphs in polynomial time, DECK CHECKING for interval graphs is easily done in polynomial time. Since the number of interval graphs that can be obtained from an interval graph by adding a vertex and edges incident to it can be exponentially large, developing polynomial time algorithms for LEGITIMATE DECK, PREIMAGE CONSTRUCTION, and PREIMAGE COUNTING on interval graphs is not trivial. We present that these three problems are solvable in polynomial time on interval graphs. (C) 2010 Elsevier B.V. All rights reserved.

We investigate connected proper interval graphs without vertex labels. We first give the number of connected proper interval graphs of n vertices. Using this result, a simple algorithm that generates a connected proper interval graph uniformly at random up to isomorphism is presented. Finally an enumeration algorithm of connected proper interval graphs is proposed. The algorithm is based on reverse search, and it outputs each connected proper interval graph in O(1) time.

We discuss the problems to list, sample, and count the chordal graphs with edge constraints. The objects we look at are chordal graphs sandwiched by a given pair of graphs where we assume that at least one of the input graphs is chordal. The setting is a natural generalization of chordal completions and deletions. For the listing problem, we give an efficient algorithm running in polynomial time per output with polynomial space. As for the sampling problem, we give two clues that indicate that a random sampling is not easy. The first clue is that we show #P-completeness results for counting problems. The second clue is that we give an instance for which a natural Markov chain suffers from an exponential mixing time. These results provide a unified viewpoint from algorithms' theory to problems arising from various areas such as statistics, data mining, and numerical computation. (C) 2010 Elsevier B.V. All rights reserved.

PREIMAGE CONSTRUCTION problem by Kratsch and Hemaspaandra naturally arose from the famous graph reconstruction conjecture. It deals with the algorithmic aspects of the conjecture. We present an O(n(8)) time algorithm for PREIMAGE, CONSTRUCTION on permutation graphs, where n is the number of graphs in the input. Since each graph of the input has n - 1 vertices and O(n(2)) edges, the input size is O(n(3)). There are polynomial time isomorphism Algorithms for permutation graphs. However time number of permutation graphs obtained by adding a vertex to a permutation graph is generally exponentially large. Thus exhaustive checking of these graphs does not achieve any polynomial time algorithm. Therefore reducing the number of preimage candidates is the key point.

The graph reconstruction conjecture is a long-standing open problem in graph theory. The conjecture has been verified for all graphs with at most 11 vertices. Further, the conjecture has been verified for regular graphs, trees, disconnected graphs, unit interval graphs, separable graphs with no pendant vertex, outer-planar graphs, and unicyclic graphs. We extend the list of graph classes for which the conjecture holds. We give a proof that bipartite permutation graphs are reconstructible.

We investigate connected proper interval graphs without vertex labels. We first give the number of connected proper interval graphs of n vertices. Using it, a simple algorithm that generates a connected proper interval graph uniformly at random up to isomorphism is presented. Finally an enumeration algorithm of connected proper interval graphs is proposed. The algorithm is based on the reverse search, and it outputs each connected proper interval graph in O(1) time.

The graph reconstruction conjecture is a long-standing open problem in graph theory. There are many algorithmic studies related it besides mathematical studies, such as DECK CHECKING, LEGITIMATE DECK, PREIMAGE CONSTRUCTION, and PREIMAGE COUNTING. We study these algorithmic problems limiting the graph class to interval graphs. Since we can solve GRAPH ISOMORPHISM for interval graphs in polynomial time, DECK CHECKING for interval graphs is easily done in polynomial time. Since the number of interval graphs that can be obtained from an interval graph by adding a vertex and edges incident to it can be exponentially large, developing polynomial time algorithms for LEGITIMATE DECK, PREIMACE CONSTRUCTION, and PREIMAGE COUNTING on interval graphs is not trivial. We present that these three problems are solvable in polynomial time on interval graphs.

We discuss the problems to list, sample, and count the chordal graphs with edge constraints. The objects we look at are chordal graphs sandwiched by a given pair of graphs where we assume at least one of the input pair is chordal. The setting is a natural generalization of chordal completions and deletions. For the listing problem, we give an efficient algorithm running in polynomial time per output with polynomial space. As for the sampling problem, we give two clues that seem to imply that a random sampling is not easy. The first clue is that we show #P-completeness results for counting problems. The second clue is that we give an instance for which a natural Markov chain suffers from an exponential mixing time. These results provide a unified viewpoint from algorithms theory to problems arising from various areas such as statistics, data mining, and numerical computation.

A chordal graph is a graph which contains no chordless cycle of at least four edges as an induced subgraph. The class of chordal graphs contains many famous graph classes such as trees, interval graphs, and split graphs, and is also a subclass of perfect graphs. In this paper, we address the problem of enumerating all labeled chordal graphs included in a given graph. We think of some variations of this problem. First we introduce an algorithm to enumerate all connected labeled chordal graphs in a complete graph of n vertices. Next, we extend the algorithm to an algorithm to enumerate all labeled chordal graphs in a n-vertices complete graph. Then, we show that we can use, with small changes, these algorithms to generate all (connected or not necessarily connected) labeled chordal graphs in arbitrary graph. All our algorithms are based on reverse search method, and time complexities to generate a chordal graph are O(l), and also O(l) delay. Additionally, we present an algorithm to generate every clique of a given chordal graph in constant time. Using these algorithms we obtain combinatorial Gray code like sequences for these graph structures in which the differences between two consecutive graphs are bounded by a constant size.

We propose three algorithms for enumeration problems; given a graph G, to find every chordal supergraph (in K-n) of G, to find every interval supergraph (in K.) of G, and to find every interval subgraph of G in K-n. The algorithms are based on the reverse search method. A graph is chordal if and only if it has no induced chordless cycle of length more than three. A graph is an interval graph if and only if it has an interval representation. To the best of our knowledge, ours are the first results about the enumeration problems to list every interval subgraph of the input graph and to list every chordal/interval supergraph of the input graph in polynomial time. The time complexities of the first algorithm is O((n + m)(2)) for each output graph, and those for the rest two algorithms are O(n(3)) for each output graph, where m is the number of edges of input graph G. We also show that a straight-forward depth-first search type algorithm is not appropriate for these problems.

We present two efficient algorithms for solving the electric power transaction problem. The electric power transaction problem appears when maximizing the social benefit on electric power transactions among some private companies. The problem is a special case of the minimum cost flow problem defined on a network with many leaves, where each leaf corresponds to a (private) company who wants to sell or buy electric power. Our first algorithm is based on the minimum mean cycle canceling algorithm and the second algorithm uses a linear time median finding algo-rithm. The first algorithm finds an optimal solution in O(n log n k5 log (kC)) time where n is the number of leaves, k is the number of non-leaf vertices and C is the highest electric power price per unit that companies may offer. The time complexity of the second algorithm is bounded by O((n + k3)2kk!) time, which is linear in n. In many practical instances, k is small and n is very large, hence these algorithms solve the problem more efficiently than the ordinary network flow algorithms. © Springer-Verlag Berlin Heidelberg 2005.

Amazons is a perfect information board game with simple rules and large branching factors. Two players alternately move chess queen-like pieces and block squares on a 10 x 10 playing field. The player who makes the last move wins. Amazons endgames usually decompose into independent subgames. Therefore, the game is a natural testbed for combinatorial game theory. It was known that determining the winner of simple generalized Amazons endgames is NP-equivalent. This paper presents two proofs for the PSPACE-completeness of the generalized version of the full game.

Peg solitaire is a one player game using pegs and a board with some holes. The game is classical, and nowadays sold in many parts of the world under the trade name of Hi-Q. In this paper, we dealt with the peg solitaire problem as an integer programming problem. We proposed algorithms based on the backtrack search method and relaxation methods for integer programming problem. The algorithms first solve relaxed problems and get an upper bound of the number of jumps for each jump position. This upper bound saves much time at the next stage of backtrack searching. While solving the relaxed problems, we can prove many peg solitaire problems are infeasible. We proposed two types of backtrack searching, forward-only searching and forward-backward searching. The performance of these two methods highly depends on the symmetricity and the length of the sequence of required jumps. Our algorithm can solve all the peg solitaire problem instances we tried and the total computational time is less than 20 minutes on an ordinary notebook personal computer.