Fast Optimal Clearing of Capped-Chain Barter Exchanges
Authors: Benjamin Plaut, John Dickerson, Tuomas Sandholm
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | On that real data and demographically-accurate generated data, our new solver scales significantly better than the prior leading approaches. |
| Researcher Affiliation | Academia | Benjamin Plaut Carnegie Mellon University bplaut@andrew.cmu.edu John P. Dickerson Carnegie Mellon University dickerson@cs.cmu.edu Tuomas Sandholm Carnegie Mellon University sandholm@cs.cmu.edu |
| Pseudocode | No | The paper describes algorithmic concepts like Bellman-Ford and branch-and-price methods in prose, but it does not include any structured pseudocode blocks or algorithm listings. |
| Open Source Code | No | The paper does not provide any specific links to source code repositories or explicit statements about the release of their implementation's code. |
| Open Datasets | Yes | We first test on real data from the United Network for Organ Sharing (UNOS) nationwide kidney exchange, which now contains 143 transplant centers... We also used demographically-accurate generated data, sampled from the set of all pairs and altruists who had entered the UNOS exchange by Nov. 2014. |
| Dataset Splits | No | The paper describes experiments on 'real UNOS match runs' and 'Generated UNOS data' but does not specify any training, validation, or test dataset splits, percentages, or cross-validation methodologies. |
| Hardware Specification | No | On each problem instance, each solver was given access to 28GB of RAM, 4 cores, and 60 minutes of wall time. |
| Software Dependencies | No | The paper mentions types of solvers (e.g., 'integer program solver', 'branch and price') but does not specify any particular software names with version numbers for dependencies or the solvers used in their experiments. |
| Experiment Setup | Yes | The cycle cap was set to 3, as is almost ubiquitous in practice (also at UNOS). We varied the chain cap. On each problem instance, each solver was given access to 28GB of RAM, 4 cores, and 60 minutes of wall time. |