Sprague-Grundy values and complexity for LCTR

Given a Young diagram on $n$ boxes as a non-increasing sequence of integers, we consider the impartial combinatorial game LCTR in which moves consist of removing either the left column or top row of boxes. We show that for both normal and mis\`ere play, the optimal strategy can consist mostly of mirroring the opponent's moves. This allows for computing the Sprague-Grundy value of the given game in $O(\log(n))$ time units, where time unit allows for reading an integer, or performing a basic arithmetic operation. This improves on the previous bound of $O(n)$ time units, due to by Ili\'c (2019), which can be obtained by an improvement of the Sprague-Grundy recursion.Comment: 24 pages, 7 figures, 1 tabl

Minimizing Maximum Dissatisfaction in the Allocation of Indivisible Items under a Common Preference Graph

We consider the task of allocating indivisible items to agents, when the agents' preferences over the items are identical. The preferences are captured by means of a directed acyclic graph, with vertices representing items and an edge $(a,b)$, meaning that each of the agents prefers item $a$ over item $b$. The dissatisfaction of an agent is measured by the number of items that the agent does not receive and for which it also does not receive any more preferred item. The aim is to allocate the items to the agents in a fair way, i.e., to minimize the maximum dissatisfaction among the agents. We study the status of computational complexity of that problem and establish the following dichotomy: the problem is NP-hard for the case of at least three agents, even on fairly restricted graphs, but polynomially solvable for two agents. We also provide several polynomial-time results with respect to different underlying graph structures, such as graphs of width at most two and tree-like structures such as stars and matchings. These findings are complemented with fixed parameter tractability results related to path modules and independent set modules. Techniques employed in the paper include bottleneck assignment problem, greedy algorithm, dynamic programming, maximum network flow, and integer linear programming.Comment: 26 pages, 2 figure

Strong cliques in diamond-free graphs

A strong clique in a graph is a clique intersecting all inclusion-maximal stable sets. Strong cliques play an important role in the study of perfect graphs. We study strong cliques in the class of diamond-free graphs, from both structural and algorithmic points of view. We show that the following five NP-hard or co-NP-hard problems remain intractable when restricted to the class of diamond-free graphs: Is a given clique strong? Does the graph have a strong clique? Is every vertex contained in a strong clique? Given a partition of the vertex set into cliques, is every clique in the partition strong? Can the vertex set be partitioned into strong cliques? On the positive side, we show that the following two problems whose computational complexity is open in general can be solved in linear time in the class of diamond-free graphs: Is every maximal clique strong? Is every edge contained in a strong clique? These results are derived from a characterization of diamond-free graphs in which every maximal clique is strong, which also implies an improved Erd\H{o}s-Hajnal property for such graphs.Comment: An extended abstract of this work was accepted at WG 202

Sprague-Grundy function of symmetric hypergraphs

We consider a generalization of the classical game of $NIM$ called hypergraph $NIM$. Given a hypergraph \cH on the ground set $V = \{1, \ldots, n\}$ of $n$ piles of stones, two players alternate in choosing a hyperedge H \in \cH and strictly decreasing all piles $i\in H$. The player who makes the last move is the winner. Recently it was shown that for many classes of hypergraphs the Sprague-Grundy function of the corresponding game is given by the formula introduced originally by Jenkyns and Mayberry (1980). In this paper we characterize symmetric hypergraphs for which the Sprague-Grundy function is described by the same formula