Papers for

network planners

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Biplanar graphs with small independence number need at most nine colors

Biplanar graphs with independence number two are 9-colorable

Abstract: A graph is biplanar if it is the union of two planar graphs on the same vertex set. The largest chromatic number of a biplanar graph is known to lie between 9 and 12. The lower bound comes from Sulanke's graph, which has independence number 2, and a biplanar graph on 19 vertices with independence number 2 would have chromatic number at least 10. Gethner and Sulanke asked in 2009 whether such a graph exists. We show that it does not, and more generally that every biplanar graph with independence number at most 2 is 9-colorable. The proof embeds a hypothetical counterexample in the union of two sphere triangulations, enumerates with SAT modulo symmetries the 3271 graphs that pass a necessary filter for the complement of such a union, and shows with a SAT solver that none of them is such a complement; a matching argument reduces the general statement to this computation and one further case on 18 vertices. The computational part of the proof, including the completeness of the enumeration and every refutation, is checked in Lean 4, assuming three classical facts about planar graphs. The Lean development, the SAT instances, and the enumeration certificates are available on Zenodo.

Wed 23 SeptLogic in Computer Science
The gist
This paper studies a type of graph made by combining two graphs that can be drawn without crossing lines. When coloring such graphs—assigning colors so that connected points differ—the question is how many colors are needed if no three points are all separate from each other (independence number 2). The authors prove that these graphs can always be colored with at most nine colors, resolving an open question. They reached this conclusion by combining mathematical reasoning with computer checks verified by formal proof software.
Open → 2609.28102v1

Moving geometric objects to ensure connected or dense intersection graphs

Moving Geometric Objects to Render Their Intersection Graph Connected or Locally Dense

Abstract: In this paper, we study graph editing problems on geometric intersection graphs. For a tuple $\mathcal{S}=(S_1,\dots,S_n)$ of geometric objects in some Euclidean space, let $G_\mathcal{S}$ be their intersection graph. We study the problem of finding a tuple $D=(d_1,\dots,d_n)$ of movement vectors such that the resulting intersection graph $G_{\mathcal{S}+D}$ (after moving, for every $i \in \{1,\dots,n\}$, object $S_i$ by $d_i$) has a predefined property and the total movement distance $|D|$ is minimum. In the weighted version, we are also given a weight vector $w=(w_1,\dots,w_n)$ with positive entries, and the objective is to minimise the total weighted movement distance $|w \cdot D|$. We first consider the property locally dense, which we define as containment of a $k$-clique. Given $n$ weighted intervals, we solve the problem with respect to this property in $O(k^{1/3} n \log^{1+\varepsilon} n)$ time for any $\varepsilon>0$. We then consider $k$-connectivity for $1\le k \le n-1$. Given $n$ unweighted unit intervals, we solve the problem in $O(n^2 \log n)$ time and, for $k=1$, in $O(n\log n)$ time. For $k=1$, we prove strong NP-hardness on intervals of arbitrary length and on weighted unit disks (with only two distinct weights), and weak NP-hardness on weighted intervals (even when lengths equal weights).

Sat 19 SeptComputational GeometryData Structures and Algorithms
The gist
This paper looks at how to move shapes like intervals or disks just enough to make their overlaps form graphs with certain features, such as being connected or having a dense cluster of overlaps. The authors focus on minimizing the total movement needed to achieve these properties. They develop algorithms to solve this with different shapes and connectivity goals, and also show some problems are hard to solve efficiently. This research helps understand how to control overlaps by small adjustments efficiently.
Open → 2609.22958v1

Core membership testing for minimum-cost network spanning games

Core stability recognition for minimum-cost spanning tree games: Parameterized perspective

Abstract: Minimum-cost spanning tree game (MSTG) is a cooperative game played on an undirected edge-weighted graph $(G,w)$ representing the network, where each vertex corresponds to a player and each edge has an associated cost~$w$. A distinguished vertex $s \in V(G)$ represents the supply or source. For any coalition of players $S$, the characteristic cost function $c(S)$ is defined as the minimum cost of a spanning tree with respect to $w$, connecting exactly the vertices in $S \cup \{s\}$. In this paper we study the computational complexity of deciding core membership for MSTG. In general, deciding whether a given allocation is in the core is \textsf{coNP}-hard~(Faigle et al.,International Journal of Game Theory,1997). We study the core recognition problem under the name {\sc MSTG Core Non-Membership}. We extend the hardness to graphs which are very close to being planar. On the positive side, we present several algorithmic results within the framework of parameterized complexity. We show that {\sc MSTG Core Non-Membership} is fixed-parameter tractable when parameterized by the support size of the allocation. Turning into structural parameters of graphs, we show that the problem admits an FPT algorithm parameterized by treewidth and signed neighborhood diversity. Last but not least, we investigate kernelization. While in general graphs, under standard complexity-theoretical assumptions, {\sc MSTG Core Non-Membership} does not admit a polynomial kernel parameterized by the vertex cover number, we design a cubic kernel in planar graphs. Furthermore, in general graphs, we obtain quadratic kernel for signed neighborhood diversity and linear kernel for the parameter feedback edge number.

Wed 16 SeptComputer Science and Game TheoryComputational Complexity
The gist
This paper looks at a problem where different players in a network share costs for connecting to a supply point through a cheapest possible tree of paths. The key question is how to decide if a specific way of sharing costs is stable—meaning no group of players wants to change it because they could do better on their own. The authors show that this decision is hard in general but find special ways to solve it efficiently by focusing on specific graph properties or how many players have non-zero cost shares. They also design smaller equivalent problems for some types of networks to speed up the process.
Open → 2609.18807v1

Strategyproof methods improve pathway building between blocked regions

Strategyproof Mechanisms for Connecting Impassable Regions

Abstract: We study strategyproof mechanisms for building a pathway between two regions of a line segment separated by an obstacle. Each of the $n$ agents has a private location within its region and may use either its original route to a facility or the new pathway, whose traversal cost is a fraction $k\in[0,1)$ of its length. We seek strategyproof (SP) and group-strategyproof (GSP) mechanisms that approximately minimize maximum cost or social cost. After characterizing optimal pathways for both objectives, we establish a tight deterministic maximum-cost approximation ratio of $\frac{2}{1+k}$ and a deterministic social-cost upper bound of $\frac{n}{1+k(n-1)}$, together with complementary lower bounds. Both upper bounds are achieved by GSP mechanisms. We then study randomized mechanisms under strategyproofness in expectation. A power-proportional mechanism achieves a social-cost approximation ratio at most $5$, independent of $n$ and $k$, with a tight guarantee of $3$ for this mechanism when $k=0$. We prove randomized lower bounds of $\frac{3+2k}{2+3k}$ for maximum cost and $\max\big\{1,\frac{285}{263+385k}\big\}$ for social cost, the latter for $n\ge7$. Finally, we improve several bounds for the real-line pathway model of [Chan and Wang, AAMAS 2023]. Our deterministic maximum-cost lower bound of $2$ matches the upper bound obtainable from [Qin, Fang, and Liu, COCOA 2024]. We strengthen the deterministic social-cost lower bound from $\frac32$ to $2$ under SP and to $\max\{2,n-1\}$ under GSP. For randomized social cost, we sharpen the guarantee of Chan and Wang's proportional mechanism from $6$ to $3$ and raise their lower bound from $1.02$ to $\frac{285}{263}\approx1.08365$ for $n\ge7$.

Tue 8 SeptComputer Science and Game Theory
The gist
This paper looks at how to build a route connecting two separated areas when there's an obstacle between them, with agents whose exact positions are private information. The challenge is to design systems that encourage truthful reporting of locations while keeping travel costs low, either for the worst-off agent or for everyone combined. The authors find best possible trade-offs for deterministic methods and also explore randomized approaches with guaranteed performance. They further improve known results from earlier research in this area.
Open → 2609.08488v1