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Combinatorial Ski Rental Problem: Robust and Learning-Augmented Algorithms
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Introduces the Combinatorial Ski Rental problem and proposes a randomized online algorithm, Sorted Optimal Amortized Cost (SOAC), for irrevocable buy-or-rent decisions over multiple items.
Problem
Online decision-making where multiple items can be rented or purchased individually or in combination, with irrevocable buy-or-rent decisions made without knowing the time horizon.
Approach
Generalizes the classic ski rental problem to combinatorial (multi-item, bundle-pricing) settings and proposes a randomized algorithm, SOAC, based on sorted optimal amortized costs; the abstract mentions no further details.
Experimental setup
Builds on: ski rental problem
Closest papers by meaning
- Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis (ICML 2023 · similarity 0.93)
- Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem (AAAI 2024 · similarity 0.93)
- Competitive Analysis for Two-Level Ski-Rental Problem (AAAI 2021 · similarity 0.92)
- Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice (NeurIPS 2020 · similarity 0.91)
- Learning-Augmented Algorithms for the Bahncard Problem (NeurIPS 2024 · similarity 0.90)
- Time Fairness in Online Knapsack Problems (ICLR 2024 · similarity 0.82)
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