English
Related papers

Related papers: Fine-Grained Completeness for Optimization in P

200 papers

We study optimization problems that are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. Specifically, we focus on Maximum Independent…

Data Structures and Algorithms · Computer Science 2008-10-29 Marek Cygan , Lukasz Kowalik , Marcin Pilipczuk , Mateusz Wykurz

It has been observed in many places that constant-factor approximable problems often admit polynomial or even linear problem kernels for their decision versions, e.g., Vertex Cover, Feedback Vertex Set, and Triangle Packing. While there…

Computational Complexity · Computer Science 2015-03-13 Stefan Kratsch

Maximum surjective constraint satisfaction problems (Max-Sur-CSPs) are computational problems where we are given a set of variables denoting values from a finite domain B and a set of constraints on the variables. A solution to such a…

Computational Complexity · Computer Science 2011-10-14 Walter Bach , Hang Zhou

Constraint satisfaction problems (CSPs) are ubiquitous in theoretical computer science. We study the problem of StrongCSPs, i.e. instances where a large induced sub-instance has a satisfying assignment. More formally, given a CSP instance…

Data Structures and Algorithms · Computer Science 2022-05-24 Suprovat Ghoshal , Anand Louis

The class $(r,2)$-CSP, or simply Max 2-CSP, consists of constraint satisfaction problems with at most two $r$-valued variables per clause. For instances with $n$ variables and $m$ binary clauses, we present an $O(n r^{5+19m/100})$-time…

Discrete Mathematics · Computer Science 2008-03-26 Alexander D. Scott , Gregory B. Sorkin

A subset of Q^n is called semilinear (or piecewise linear) if it is Boolean combination of linear half-spaces. We study the computational complexity of the constraint satisfaction problem (CSP) over the rationals when all the constraints…

Computational Complexity · Computer Science 2018-10-30 Manuel Bodirsky , Marcello Mamino

This paper continues the functional approach to the P-versus-NP problem, begun in [1]. Here we focus on the monoid RM_2^P of right-ideal morphisms of the free monoid, that have polynomial input balance and polynomial time-complexity. We…

Group Theory · Mathematics 2016-05-12 J. C. Birget

In this paper, we define the reoptimization variant of the closest substring problem (CSP) under sequence addition. We show that, even with the additional information we have about the problem instance, the problem of finding a closest…

Data Structures and Algorithms · Computer Science 2016-03-09 Jeffrey Aborot , Henry Adorna , Jhoirene Clemente

Many natural combinatorial problems can be expressed as constraint satisfaction problems. This class of problems is known to be NP-complete in general, but certain restrictions on the form of the constraints can ensure tractability. The…

Computational Complexity · Computer Science 2020-10-05 Dmitriy Zhuk

We study sparsity in the max-plus algebraic setting. We seek both exact and approximate solutions of the max-plus linear equation with minimum cardinality of support. In the former case, the sparsest solution problem is shown to be…

Optimization and Control · Mathematics 2019-06-05 Anastasios Tsiamis , Petros Maragos

In the Boolean maximum constraint satisfaction problem - Max CSP$(\Gamma)$ - one is given a collection of weighted applications of constraints from a finite constraint language $\Gamma$, over a common set of variables, and the goal is to…

Computational Complexity · Computer Science 2020-02-11 Bart M. P. Jansen , Michał Włodarczyk

We develop a polynomial time $\Omega\left ( \frac 1R \log R \right)$ approximate algorithm for Max 2CSP-$R$, the problem where we are given a collection of constraints, each involving two variables, where each variable ranges over a set of…

Data Structures and Algorithms · Computer Science 2015-04-07 Guy Kindler , Alexandra Kolla , Luca Trevisan

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

In this work we revisit the elementary scheduling problem $1||\sum p_j U_j$. The goal is to select, among $n$ jobs with processing times and due dates, a subset of jobs with maximum total processing time that can be scheduled in sequence…

Data Structures and Algorithms · Computer Science 2025-07-23 Nick Fischer , Leo Wennmann

Mixed-integer optimisation problems can be computationally challenging. Here, we introduce and analyse two efficient algorithms with a specific sequential design that are aimed at dealing with sampled problems within this class. At each…

Optimization and Control · Mathematics 2023-03-07 Mohammadreza Chamanbaz , Roland Bouffanais

Assuming that P is not equal to NP, the worst-case run time of any algorithm solving an NP-complete problem must be super-polynomial. But what is the fastest run time we can get? Before one can even hope to approach this question, a more…

Data Structures and Algorithms · Computer Science 2026-01-09 Jesper Nederlof

Raghavendra (STOC 2008) gave an elegant and surprising result: if Khot's Unique Games Conjecture (STOC 2002) is true, then for every constraint satisfaction problem (CSP), the best approximation ratio is attained by a certain simple…

Data Structures and Algorithms · Computer Science 2010-11-01 Yuichi Yoshida

We provide polynomial-time approximately optimal Bayesian mechanisms for makespan minimization on unrelated machines as well as for max-min fair allocations of indivisible goods, with approximation factors of $2$ and $\min\{m-k+1,…

Computer Science and Game Theory · Computer Science 2014-05-26 Constantinos Daskalakis , S. Matthew Weinberg

In the Demand Strip Packing problem (DSP), we are given a time interval and a collection of tasks, each characterized by a processing time and a demand for a given resource (such as electricity, computational power, etc.). A feasible…

Data Structures and Algorithms · Computer Science 2021-05-20 Waldo Gálvez , Fabrizio Grandoni , Afrouz Jabal Ameli , Kamyar Khodamoradi

In 1991, Edelsbrunner and Tan gave an O(n^2) algorithm for finding the MinMax Length triangulation of a set of points in the plane. In this paper we resolve one of the open problems stated in that paper, by showing that finding a MaxMin…

Computational Geometry · Computer Science 2012-08-02 Sándor P. Fekete