On the Approximability of Unsplittable Flow on a Path with Time Windows
March 22, 2025 Β· Declared Dead Β· π Conference on Integer Programming and Combinatorial Optimization
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Alexander Armbruster, Fabrizio Grandoni, Edin HusiΔ, Antoine Tinguely, Andreas Wiese
arXiv ID
2503.17802
Category
cs.DS: Data Structures & Algorithms
Citations
2
Venue
Conference on Integer Programming and Combinatorial Optimization
Last Checked
4 months ago
Abstract
In the Time-Windows Unsplittable Flow on a Path problem (twUFP) we are given a resource whose available amount changes over a given time interval (modeled as the edge-capacities of a given path $G$) and a collection of tasks. Each task is characterized by a demand (of the considered resource), a profit, an integral processing time, and a time window. Our goal is to compute a maximum profit subset of tasks and schedule them non-preemptively within their respective time windows, such that the total demand of the tasks using each edge $e$ is at most the capacity of $e$. We prove that twUFP is $\mathsf{APX}$-hard which contrasts the setting of the problem without time windows, i.e., Unsplittable Flow on a Path (UFP), for which a PTAS was recently discovered [Grandoni, MΓΆmke, Wiese, STOC 2022]. Then, we present a quasi-polynomial-time $2+\varepsilon$ approximation for twUFP under resource augmentation. Our approximation ratio improves to $1+\varepsilon$ if all tasks' time windows are identical. Our $\mathsf{APX}$-hardness holds also for this special case and, hence, rules out such a PTAS (and even a QPTAS, unless $\mathsf{NP}\subseteq\mathrm{DTIME}(n^{\mathrm{poly}(\log n)})$) without resource augmentation.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted