Research map / Bandits and online learning / Online convex optimization and games
Allocation Problems in Ride-Sharing Platforms: Online Matching With Offline Reusable Resources
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the LP-guided simulation-based adaptive algorithm | OM-RR-KAD · OM-RR-KAD | competitive ratio: \frac{1}{2}-\epsilon | Helped |
| Restrict the algorithm to be non-adaptive while using the benchmark LP | OM-RR-KAD · OM-RR-KAD | competitive ratio: \frac{1}{2}+o(1) | Hurt |
| Use LP-based assignment instead of choosing an available neighbor uniformly at random | ALG-LP and sCLP · NYC yellow cabs, January 2013 test days | average weight of matching | Helped |
| Use distributional information in the LP-based solutions instead of greedy matching | ALG-LP and sCLP · NYC yellow cabs, January 2013 test days | average weight of matching | Helped |
| Assume a normal rather than power-law occupation-time distribution | LP-based algorithms · NYC yellow cabs, January 2013 test days | average weight of matching | No clear effect |
| Model time-varying arrivals under KAD rather than identical arrivals under KIID | LP-based algorithms · NYC yellow cabs, January 2013 test days | average weight of matching | Helped |
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