2 articles tagged with #online-algorithms. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers resolve a gap in online fair division theory by proving that proportionality up to one good (PROP1) cannot be approximated by standard greedy algorithms against adaptive adversaries, but can be achieved through randomized allocation or learning-augmented approaches with predictions.
Researchers introduce the Online Shared Supply Allocation (OSSA) problem, a theoretical framework for allocating limited resources across multiple locations before demand is known, common in humanitarian logistics and vaccine distribution. The proposed GPA algorithm achieves a 4/3-approximation ratio to optimal offline solutions, with proven tight bounds and a learning-augmented variant that incorporates forecasts.
