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Considering mean-variance portfolio problems with uncertain model parameters, we contrast the classical absolute robust optimization approach with the relative robust approach based on a maximum regret function. Although the latter problems…

Portfolio Management · Quantitative Finance 2013-05-14 Raphael Hauser , Vijay Krishnamurthy , Reha Tütüncü

We prove the #P-hardness of the counting problems associated with various satisfiability, graph and combinatorial problems, when restricted to planar instances. These problems include \begin{romannum} \item[{}] {\sc 3Sat, 1-3Sat, 1-Ex3Sat,…

Computational Complexity · Computer Science 2007-05-23 Harry B. Hunt , Madhav V. Marathe , Venkatesh Radhakrishnan , Richard E. Stearns

We study the approximability of the maximum size independent set (MIS) problem in bounded degree graphs. This is one of the most classic and widely studied NP-hard optimization problems. We focus on the well known minimum degree greedy…

Data Structures and Algorithms · Computer Science 2020-02-03 Piotr Krysta , Mathieu Mari , Nan Zhi

The parallel machine scheduling problem has been a popular topic for many years due to its theoretical and practical importance. This paper addresses the robust makespan optimization problem on unrelated parallel machine scheduling with…

Optimization and Control · Mathematics 2020-10-23 Chutong Gao , Weihao Wang , Leyuan Shi

Network reliability measures the probability that a target node is reachable from a source node in an uncertain graph, i.e., a graph where every edge is associated with a probability of existence. In this paper, we investigate the novel and…

Databases · Computer Science 2020-05-26 Xiangyu Ke , Arijit Khan , Mohammad Al Hasan , Rojin Rezvansangsari

For decision making under uncertainty, min-max regret has been established as a popular methodology to find robust solutions. In this approach, we compare the performance of our solution against the best possible performance had we known…

Optimization and Control · Mathematics 2021-11-25 Marc Goerigk , Michael Hartisch

This paper considers pairs of optimization problems that are defined from a single input and for which it is desired to find a good approximation to either one of the problems. In many instances, it is possible to efficiently find an…

Data Structures and Algorithms · Computer Science 2009-09-11 David Eppstein

The maximum independent set problem is a classic optimization problem that has also been studied quite intensively in the distributed setting. While the problem is hard to approximate in general, there are good approximation algorithms…

Data Structures and Algorithms · Computer Science 2025-06-13 Salwa Faour , Fabian Kuhn

The NP-hard Metric Dimension problem is to decide for a given graph G and a positive integer k whether there is a vertex subset of size at most k that separates all vertex pairs in G. Herein, a vertex v separates a pair {u,w} if the…

Computational Complexity · Computer Science 2012-11-08 Sepp Hartung , André Nichterlein

We address the problem of sequential prediction with expert advice in a non-stationary environment with long-term memory guarantees in the sense of Bousquet and Warmuth [4]. We give a linear-time algorithm that improves on the best known…

Machine Learning · Computer Science 2021-06-25 James Robinson , Mark Herbster

We study various discrete nonlinear combinatorial optimization problems in an online learning framework. In the first part, we address the question of whether there are negative results showing that getting a vanishing (or even vanishing…

Data Structures and Algorithms · Computer Science 2020-06-24 Evripidis Bampis , Dimitris Christou , Bruno Escoffier , Nguyen Kim Thang

In this paper, we consider the maximum $k$-edge-colorable subgraph problem. In this problem we are given a graph $G$ and a positive integer $k$, the goal is to take $k$ matchings of $G$ such that their union contains maximum number of…

Combinatorics · Mathematics 2025-10-15 Vahan Mkrtchyan

We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the $\varepsilon$-prediction framework by Cohen-Addad, d'Orsi,…

Machine Learning · Computer Science 2025-06-02 Anders Aamand , Justin Y. Chen , Siddharth Gollapudi , Sandeep Silwal , Hao Wu

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

In this paper, we develop efficient exact and approximate algorithms for computing a maximum independent set in random graphs. In a random graph $G$, each pair of vertices are joined by an edge with a probability $p$, where $p$ is a…

Data Structures and Algorithms · Computer Science 2013-08-08 Yinglei Song

We study the approximability of the NP-complete \textsc{Maximum Minimal Feedback Vertex Set} problem. Informally, this natural problem seems to lie in an intermediate space between two more well-studied problems of this type:…

Computational Complexity · Computer Science 2021-02-12 Louis Dublois , Tesshu Hanaka , Mehdi Khosravian Ghadikolaei , Michael Lampis , Nikolaos Melissinos

Most optimization problems are notoriously hard. Considerable efforts must be spent in obtaining an optimal solution to certain instances that we encounter in the real world scenarios. Often it turns out that input instances get modified…

Data Structures and Algorithms · Computer Science 2019-04-25 Mehul Kumar , Amit Kumar , C. Pandu Rangan

In this work we investigate the min-max-min robust optimization problem and the k-adaptability robust optimization problem for binary problems with uncertain costs. The idea of the first approach is to calculate a set of k feasible…

Optimization and Control · Mathematics 2023-08-16 Jannis Kurtz

In this paper, we investigate the approximability of two node deletion problems. Given a vertex weighted graph $G=(V,E)$ and a specified, or "distinguished" vertex $p \in V$, MDD(min) is the problem of finding a minimum weight vertex set $S…

Data Structures and Algorithms · Computer Science 2014-01-15 Sounaka Mishra , Ashwin Pananjady , N Safina Devi

Multiple interval graphs are variants of interval graphs where instead of a single interval, each vertex is assigned a set of intervals on the real line. We study the complexity of the MAXIMUM CLIQUE problem in several classes of multiple…

Discrete Mathematics · Computer Science 2012-03-12 Mathew C. Francis , Daniel Gonçalves , Pascal Ochem