End-to-end pareto set prediction with graph neural networks for multi-objective facility location
The facility location problems (FLPs) are a typical class of NP-hard combinatorial
optimization problems, which are widely seen in the supply chain and logistics. Many …
optimization problems, which are widely seen in the supply chain and logistics. Many …
Revisiting Priority -Center: Fairness and Outliers
In the Priority $ k $-Center problem, the input consists of a metric space $(X, d) $, an integer
$ k $, and for each point $ v\in X $ a priority radius $ r (v) $. The goal is to choose $ k …
$ k $, and for each point $ v\in X $ a priority radius $ r (v) $. The goal is to choose $ k …
Approximation algorithms for continuous clustering and facility location problems
D Chakrabarty, M Negahbani, A Sarkar - arXiv preprint arXiv:2206.15105, 2022 - arxiv.org
We consider the approximability of center-based clustering problems where the points to be
clustered lie in a metric space, and no candidate centers are specified. We call such …
clustered lie in a metric space, and no candidate centers are specified. We call such …
Tight FPT approximation for constrained k-center and k-supplier
In this work, we study a range of constrained versions of the k-supplier and k-center
problems. In the classical (unconstrained) k-supplier problem, we are given a set of clients C …
problems. In the classical (unconstrained) k-supplier problem, we are given a set of clients C …
Parameterized approximation algorithms for k-center clustering and variants
S Bandyapadhyay, Z Friggstad… - Proceedings of the AAAI …, 2022 - ojs.aaai.org
Abstract k-center is one of the most popular clustering models. While it admits a simple 2-
approximation in polynomial time in general metrics, the Euclidean version is NP-hard to …
approximation in polynomial time in general metrics, the Euclidean version is NP-hard to …
Fully dynamic clustering and diversity maximization in doubling metrics
We present deterministic approximation algorithms for some variants of center-based
clustering and related problems in the fully dynamic setting, where the pointset evolves …
clustering and related problems in the fully dynamic setting, where the pointset evolves …
Fault-tolerant -Supplier with Outliers
D Chakrabarty, L Cote, A Sarkar - arXiv preprint arXiv:2310.07208, 2023 - arxiv.org
We present approximation algorithms for the Fault-tolerant $ k $-Supplier with Outliers
($\mathsf {F} k\mathsf {SO} $) problem. This is a common generalization of two known …
($\mathsf {F} k\mathsf {SO} $) problem. This is a common generalization of two known …
Robust k-center with two types of radii
D Chakrabarty, M Negahbani - Mathematical Programming, 2023 - Springer
In the non-uniform k-center problem, the objective is to cover points in a metric space with
specified number of balls of different radii. Chakrabarty, Goyal, and Krishnaswamy [ICALP …
specified number of balls of different radii. Chakrabarty, Goyal, and Krishnaswamy [ICALP …
Graph Burning and Non-uniform k-centers for Small Treewidth
M Lieskovský, J Sgall - … Workshop on Approximation and Online Algorithms, 2022 - Springer
We study the graph burning problem and give a polynomial-time approximation scheme
(PTAS) for arbitrary graphs of constant treewidth. This significantly extends the previous …
(PTAS) for arbitrary graphs of constant treewidth. This significantly extends the previous …
Non-Uniform -Center and Greedy Clustering
T Inamdar, K Varadarajan - arXiv preprint arXiv:2111.06362, 2021 - arxiv.org
In the Non-Uniform $ k $-Center problem, a generalization of the famous $ k $-center
clustering problem, we want to cover the given set of points in a metric space by finding a …
clustering problem, we want to cover the given set of points in a metric space by finding a …