Proportionally Fair Makespan Approximation

Authors: Michal Feldman, Jugal Garg, Vishnu V. Narayan, Tomasz Ponitka

AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our main result demonstrates that there exists a proportional mechanism (with payments) that achieves a 3/2-approximation to the optimal makespan, and this ratio is tight. To prove this result, we provide a full characterization of allocation functions that can be made proportional with payments. Furthermore, we show that for instances with normalized costs, there exists a proportional mechanism that achieves the optimal makespan.
Researcher Affiliation Collaboration Michal Feldman1,2, Jugal Garg3, Vishnu V. Narayan1, Tomasz Ponitka1 1Tel Aviv University 2Microsoft ILDC 3University of Illinois at Urbana Champaign, USA
Pseudocode Yes Algorithm 1: Anti-Diagonal Mechanism
Open Source Code No The information is insufficient. The paper does not explicitly state that source code is provided or give a link to a code repository.
Open Datasets No The information is insufficient. The paper discusses theoretical models and problem instances (e.g., 'm-by-n matrix c', 'general instances C', 'normalized instances N') rather than empirical datasets used in experiments.
Dataset Splits No The information is insufficient. The paper is theoretical and does not use empirical datasets, therefore, no dataset splits are discussed.
Hardware Specification No The information is insufficient. The paper is theoretical and does not describe any experimental setup or specific hardware used for computations.
Software Dependencies No The information is insufficient. The paper is theoretical and does not specify any software dependencies or versions.
Experiment Setup No The information is insufficient. The paper is theoretical and focuses on mathematical proofs and mechanism design, not empirical experimentation with specific setup details like hyperparameters.