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We show that any submodular minimization (SM) problem defined on a linear constraint set with constraints having up to two variables per inequality, are 2-approximable in polynomial time. If the constraints are monotone (the two variables…

Discrete Mathematics · Computer Science 2017-05-01 Dorit S. Hochbaum

We present a dynamic programming algorithm for selecting a representative subset of size $k$ from a given set with $n$ points such that the Riesz $s$-energy is near minimized. While NP-hard in general dimensions, the one-dimensional case…

Data Structures and Algorithms · Computer Science 2025-02-11 Michael Emmerich

This paper introduces the Simultaneous assignment problem. Let us given a graph with a weight and a capacity function on its edges, and a set of its subgraphs along with a degree upper bound function for each of them. We are also given a…

Data Structures and Algorithms · Computer Science 2023-01-24 Péter Madarasi

We present a computational methodology for obtaining rotationally symmetric sets of points satisfying discrete geometric constraints, and demonstrate its applicability by discovering new solutions to some well-known problems in…

Discrete Mathematics · Computer Science 2025-06-03 Bernardo Subercaseaux , Ethan Mackey , Long Qian , Marijn J. H. Heule

In subset selection we search for the best linear predictor that involves a small subset of variables. From a computational complexity viewpoint, subset selection is NP-hard and few classes are known to be solvable in polynomial time. Using…

Optimization and Control · Mathematics 2020-02-07 Alberto Del Pia , Santanu S. Dey , Robert Weismantel

Many discrete optimization problems amount to selecting a feasible set of edges of least weight. We consider in this paper the context of spatial graphs where the positions of the vertices are uncertain and belong to known uncertainty sets.…

Data Structures and Algorithms · Computer Science 2022-09-27 Marin Bougeret , Jérémy Omer , Michael Poss

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum…

Quantum Physics · Physics 2024-06-19 Dhrumil Patel , Patrick J. Coles , Mark M. Wilde

We consider the robust version of items selection problem, in which the goal is to choose representatives from a family of sets, preserving constraints on the allowed items' combinations. We prove NP-hardness of the deterministic version,…

Discrete Mathematics · Computer Science 2019-07-23 Maciej Drwal

We study approximation algorithms for several variants of the MaxCover problem, with the focus on algorithms that run in FPT time. In the MaxCover problem we are given a set N of elements, a family S of subsets of N, and an integer K. The…

Data Structures and Algorithms · Computer Science 2013-09-18 Piotr Skowron , Piotr Faliszewski

In the Strip Packing problem (SP), we are given a vertical half-strip $[0,W]\times[0,\infty)$ and a set of $n$ axis-aligned rectangles of width at most $W$. The goal is to find a non-overlapping packing of all rectangles into the strip such…

Data Structures and Algorithms · Computer Science 2022-05-09 Arindam Khan , Aditya Lonkar , Arnab Maiti , Amatya Sharma , Andreas Wiese

We study the Parallel Task Scheduling problem $Pm|size_j|C_{\max}$ with a constant number of machines. This problem is known to be strongly NP-complete for each $m \geq 5$, while it is solvable in pseudo-polynomial time for each $m \leq 3$.…

Computational Complexity · Computer Science 2017-05-15 Sören Henning , Klaus Jansen , Malin Rau , Lars Schmarje

Various real-world problems consist of partitioning a set of locations into disjoint subsets, each subset spread in a way that it covers the whole set with a certain radius. Given a finite set S, a metric d, and a radius r, define a subset…

Data Structures and Algorithms · Computer Science 2023-02-08 Eran Rosenbluth

We investigate error bounds for numerical solutions of divergence structure linear elliptic PDEs on compact manifolds without boundary. Our focus is on a class of monotone finite difference approximations, which provide a strong form of…

Numerical Analysis · Mathematics 2023-06-05 Brittany Froese Hamfeldt , Axel G. R. Turnquist

A dominating set D in a graph G is a subset of its vertices such that every vertex of the graph which does not belong to set D is adjacent to at least one vertex from set D. A set of vertices of graph G is a global dominating set if it is a…

Discrete Mathematics · Computer Science 2024-10-25 Ernesto Parra Inza , Nodari Vakhania , Jose M. Sigarreta Almira , Frank A. Hernández Mira

In a \emph{separability problem}, we are given two sets $K$ and $L$ from a class $\mathcal{C}$, and we want to decide whether there exists a set $S$ from a class $\mathcal{S}$ such that $K\subseteq S$ and $S\cap L=\emptyset$. In this case,…

Formal Languages and Automata Theory · Computer Science 2025-07-02 Elias Rojas Collins , Chris Köcher , Georg Zetzsche

A {\em dominating set} of a graph $G=(V,E)$ is a subset of vertices $S\subseteq V$ such that every vertex $v\in V\setminus S$ has at least one neighbor in $S$. Finding a dominating set with the minimum cardinality in a connected graph…

Discrete Mathematics · Computer Science 2022-11-23 Frank Hernandez , Ernesto Parra , Jose Maria Sigarreta , Nodari Vakhania

Many combinatorial optimization problems can be formulated as the search for a subgraph that satisfies certain properties and minimizes the total weight. We assume here that the vertices correspond to points in a metric space and can take…

Data Structures and Algorithms · Computer Science 2024-12-25 Marin Bougeret , Jérémy Omer , Michael Poss

In this paper, we propose the first exact algorithm for minimizing the difference of two submodular functions (D.S.), i.e., the discrete version of the D.C. programming problem. The developed algorithm is a branch-and-bound-based algorithm…

Data Structures and Algorithms · Computer Science 2011-08-23 Yoshinobu Kawahara , Takashi Washio

Semidefinite programs (SDP) are one of the most versatile frameworks in numerical optimization, serving as generalizations of many conic programs and as relaxations of NP-hard combinatorial problems. Their main drawback is their…

Optimization and Control · Mathematics 2022-02-28 Biel Roig-Solvas , Mario Sznaier

In this paper, we study a class of fractional semi-infinite polynomial programming (FSIPP) problems, in which the objective is a fraction of a convex polynomial and a concave polynomial, and the constraints consist of infinitely many convex…

Optimization and Control · Mathematics 2021-05-18 Feng Guo , Liguo Jiao