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The aim of the paper is to compare different approximation algorithms for the travelling salesperson problem. We pick the most popular and widespread methods known in the literature and contrast them with a novel approach (the polygonal…

Combinatorics · Mathematics 2021-09-03 Mateusz Krukowski , Filip Turoboś

TSP (Traveling Salesman Problem), a classic NP-complete problem in combinatorial optimization, is of great significance in multiple fields. Exact algorithms for TSP are not practical due to their exponential time cost. Thus, approximate…

Data Structures and Algorithms · Computer Science 2019-11-12 Yang Li , Junbin Gao , Mingyuan Bai , Chengjun Li , Gang Liu

The traveling salesman problem (TSP) is one of the most challenging NP-hard problems. It has widely applications in various disciplines such as physics, biology, computer science and so forth. The best known approximation algorithm for…

Data Structures and Algorithms · Computer Science 2016-12-13 Wenhong Tian , Chaojie Huang , Xinyang Wang , Qin Xiong

We give a constant factor approximation algorithm for the asymmetric traveling salesman problem when the support graph of the solution of the Held-Karp linear programming relaxation has bounded orientable genus.

Data Structures and Algorithms · Computer Science 2011-01-17 Shayan Oveis Gharan , Amin Saberi

We study parallel algorithms for the problem of maximizing a non-negative submodular function. Our main result is an algorithm that achieves a nearly-optimal $1/2 -\epsilon$ approximation using $O(\log(1/\epsilon) / \epsilon)$ parallel…

Data Structures and Algorithms · Computer Science 2018-12-05 Alina Ene , Huy L. Nguyen , Adrian Vladu

We examine the \emph{submodular maximum coverage problem} (SMCP), which is related to a wide range of applications. We provide the first variational approximation for this problem based on the Nemhauser divergence, and show that it can be…

Machine Learning · Computer Science 2020-06-11 Jian Du , Zhigang Hua , Shuang Yang

In this paper, we study the problem of maximizing $k$-submodular functions subject to a knapsack constraint. For monotone objective functions, we present a $\frac{1}{2}(1-e^{-2})\approx 0.432$ greedy approximation algorithm. For the…

Data Structures and Algorithms · Computer Science 2023-09-18 Hao Xiao , Qian Liu , Yang Zhou , Min Li

This paper studies bilinear saddle point problems $\min_{\bf{x}} \max_{\bf{y}} g(\bf{x}) + \bf{x}^{\top} \bf{A} \bf{y} - h(\bf{y})$, where the functions $g, h$ are smooth and strongly-convex. When the gradient and proximal oracle related to…

Machine Learning · Computer Science 2021-03-16 Guangzeng Xie , Yuze Han , Zhihua Zhang

The problem of finding the maximum-weight, planar subgraph of a finite, simple graph with nonnegative real edge weights is well known in industrial and electrical engineering, systems biology, sociology and finance. As the problem is known…

Discrete Mathematics · Computer Science 2017-12-18 Diane Castonguay , Elisângela Silva Dias , Leslie Richard Foulds

Robust optimization is a widely studied area in operations research, where the algorithm takes as input a range of values and outputs a single solution that performs well for the entire range. Specifically, a robust algorithm aims to…

Data Structures and Algorithms · Computer Science 2020-05-19 Arun Ganesh , Bruce M. Maggs , Debmalya Panigrahi

We investigate the performance of a deterministic GREEDY algorithm for the problem of maximizing functions under a partition matroid constraint. We consider non-monotone submodular functions and monotone subadditive functions. Even though…

Discrete Mathematics · Computer Science 2019-02-22 Tobias Friedrich , Andreas Göbel , Frank Neumann , Francesco Quinzan , Ralf Rothenberger

A minimum $s$-$t$ cut in a hypergraph is a bipartition of vertices that separates two nodes $s$ and $t$ while minimizing a hypergraph cut function. The cardinality-based hypergraph cut function assigns a cut penalty to each hyperedge based…

Data Structures and Algorithms · Computer Science 2024-09-25 Vedangi Bengali , Nate Veldt

In the knapsack problem under explorable uncertainty, we are given a knapsack instance with uncertain item profits. Instead of having access to the precise profits, we are only given uncertainty intervals that are guaranteed to contain the…

Data Structures and Algorithms · Computer Science 2025-07-04 Jens Schlöter

We consider the optimal coverage problem where a multi-agent network is deployed in an environment with obstacles to maximize a joint event detection probability. The objective function of this problem is non-convex and no global optimum is…

Optimization and Control · Mathematics 2017-08-15 Xinmiao Sun , Christos G. Cassandras , Xiangyu Meng

We provide exact and approximation methods for solving a geometric relaxation of the Traveling Salesman Problem (TSP) that occurs in curve reconstruction: for a given set of vertices in the plane, the problem Minimum Perimeter Polygon (MPP)…

We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pal and Vondrak, 2008), our algorithm is…

Data Structures and Algorithms · Computer Science 2013-11-20 Yuval Filmus , Justin Ward

The optimal pricing problem is a fundamental problem that arises in combinatorial auctions. Suppose that there is one seller who has indivisible items and multiple buyers who want to purchase a combination of the items. The seller wants to…

Computer Science and Game Theory · Computer Science 2016-11-24 Takanori Maehara , Yasushi Kawase , Hanna Sumita , Katsuya Tono , Ken-ichi Kawarabayashi

In graph theory, the longest path problem is the problem of finding a simple path of maximum length in a given graph. For some small classes of graphs, the problem can be solved in polynomial time [2, 4], but it remains NP-hard on general…

Data Structures and Algorithms · Computer Science 2014-09-15 Lajos L. Pongrácz

We consider the following question. We are given a dense digraph $D$ with minimum in- and out-degree at least $\alpha n$, where $\alpha>1/2$ is a constant. The edges of $D$ are given edge costs $C(e),e\in E(D)$, where $C(e)$ is an…

Data Structures and Algorithms · Computer Science 2021-08-31 Alan Frieze

A number of recent results on optimization problems involving submodular functions have made use of the multilinear relaxation of the problem. These results hold typically in the value oracle model, where the objective function is…

Data Structures and Algorithms · Computer Science 2013-01-31 Jan Vondrak