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In this paper we introduce the concept of additive approximation schemes and apply it to load balancing problems. Additive approximation schemes aim to find a solution with an absolute error in the objective of at most $\epsilon h$ for some…

Data Structures and Algorithms · Computer Science 2020-07-21 Moritz Buchem , Lars Rohwedder , Tjark Vredeveld , Andreas Wiese

We consider the {\em Capacitated Domination} problem, which models a service-requirement assignment scenario and is also a generalization of the well-known {\em Dominating Set} problem. In this problem, given a graph with three parameters…

Discrete Mathematics · Computer Science 2015-05-18 Mong-Jen Kao , Han-Lin Chen

In this paper, we consider a finite horizon non-stationary inventory system with setup costs. We detail an algorithm to find an approximate optimal policy and the basic idea is to use numerical procedure for computing integrals involved in…

Optimization and Control · Mathematics 2023-03-16 Jianyong Liu , Wei Geng , Xiaobo Zhao

Optimization problems consist of either maximizing or minimizing an objective function. Instead of looking for a maximum solution (resp. minimum solution), one can find a minimum maximal solution (resp. maximum minimal solution). Such…

Data Structures and Algorithms · Computer Science 2018-11-08 Kaveh Khoshkhah , Mehdi Khosravian Ghadikolaei , Jerome Monnot , Florian Sikora

This thesis investigates the extent to which the optimal value of a constraint satisfaction problem (CSP) can be approximated by some sentence of fixed point logic with counting (FPC). It is known that, assuming $\mathsf{P} \neq…

Logic in Computer Science · Computer Science 2020-08-10 Jamie Tucker-Foltz

In multi-objective optimization, computing the entire non-dominated set (also known as the Pareto front or the Pareto frontier) is often intractable. However, for any multiplicative factor greater than one, an approximation set can be…

Optimization and Control · Mathematics 2026-04-30 Levin Nemesch , Stefan Ruzika , Clemens Thielen , Alina Wittmann

We consider the following two deterministic inventory optimization problems over a finite planning horizon $T$ with non-stationary demands. (a) Submodular Joint Replenishment Problem: This involves multiple item types and a single retailer…

Data Structures and Algorithms · Computer Science 2015-04-27 Viswanath Nagarajan , Cong Shi

We establish efficient approximate counting algorithms for several natural problems in local lemma regimes. In particular, we consider the probability of intersection of events and the dimension of intersection of subspaces. Our approach is…

Data Structures and Algorithms · Computer Science 2025-12-12 Ryan L. Mann , Gabriel Waite

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

We study a class of combinatorial scheduling problems characterized by a particular type of constraint often associated with electrical power or gas energy. This constraint appears in several practical applications and is expressed as a sum…

Data Structures and Algorithms · Computer Science 2023-12-27 Trung Thanh Nguyen , Khaled Elbassioni , Areg Karapetyan , Majid Khonji

Motivated by the need for, and growing interest in, modeling uncertainty in data, we introduce and study {\em stochastic minimum-norm optimization}. We have an underlying combinatorial optimization problem where the costs involved are {\em…

Data Structures and Algorithms · Computer Science 2020-11-04 Sharat Ibrahimpur , Chaitanya Swamy

Measurements and sensing implementations impose certain cost in sensor networks. The sensor selection cost optimization is the problem of minimizing the sensing cost of monitoring a physical (or cyber- physical) system. Consider a given set…

Systems and Control · Computer Science 2017-06-01 Mohammadreza Doostmohammadian , Houman Zarrabi , Hamid R. Rabiee

Inspired by regularization techniques in statistics and machine learning, we study complementary composite minimization in the stochastic setting. This problem corresponds to the minimization of the sum of a (weakly) smooth function endowed…

Machine Learning · Computer Science 2024-01-24 Alexandre d'Aspremont , Cristóbal Guzmán , Clément Lezane

$\delta$-Covering, for some covering range $\delta>0$, is a continuous facility location problem on undirected graphs where all edges have unit length. The facilities may be positioned on the vertices as well as on the interior of the…

Data Structures and Algorithms · Computer Science 2024-08-09 Tim A. Hartmann , Tom Janßen

We devise a polynomial-time approximation scheme for the classical geometric problem of finding an approximate short path amid weighted regions. In this problem, a triangulated region P comprising of n vertices, a positive weight associated…

Computational Geometry · Computer Science 2016-12-08 R Inkulu , Sanjiv Kapoor

We propose an algorithm for generating explicit solutions of multiparametric mixed-integer convex programs to within a given suboptimality tolerance. The algorithm is applicable to a very general class of optimization problems, but is most…

Optimization and Control · Mathematics 2019-06-12 Danylo Malyuta , Behcet Acikmese

We consider set covering problems where the underlying set system satisfies a particular replacement property w.r.t. a given partial order on the elements: Whenever a set is in the set system then a set stemming from it via the replacement…

Discrete Mathematics · Computer Science 2015-03-17 Friedrich Eisenbrand , Naonori Kakimura , Thomas Rothvoß , Laura Sanità

In this paper, we introduce the problem of Matroid-Constrained Vertex Cover: given a graph with weights on the edges and a matroid imposed on the vertices, our problem is to choose a subset of vertices that is independent in the matroid,…

Data Structures and Algorithms · Computer Science 2023-06-08 Chien-Chung Huang , François Sellier

We study the computational complexity of approximating general constrained Markov decision processes. Our primary contribution is the design of a polynomial time $(0,\epsilon)$-additive bicriteria approximation algorithm for finding optimal…

Data Structures and Algorithms · Computer Science 2025-02-12 Jeremy McMahan

In this paper, we propose a distributed algorithm for the minimum dominating set problem. For some especial networks, we prove theoretically that the achieved answer by our proposed algorithm is a constant approximation factor of the exact…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-05 Sharareh Alipour , Ehsan Futuhi , Shayan Karimi
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