A Polynomial-time, Truthful, Individually Rational and Budget Balanced Ridesharing Mechanism
Authors: Tatsuya Iwase, Sebastian Stein, Enrico H. Gerding
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically evaluate the performance of different mechanisms and show the advantages of our methods. Our monotone greedy mechanism satisfies all desirable properties with typically less than a 9% social cost increase compared to the optimal allocation. |
| Researcher Affiliation | Collaboration | 1Toyota Motor Europe NV/SA, Zaventem, Belgium 2University of Southampton, Southampton, United Kingdom |
| Pseudocode | Yes | Algorithm 1 GARS-NIR Algorithm 2 GARS-N Algorithm 3 Greedy Allocation |
| Open Source Code | No | The paper provides a link to an extended version on arXiv (https://arxiv.org/abs/2105.11292), which is an academic pre-print server, not a code repository. There is no other statement providing concrete access to the source code for the methodology described in the paper. |
| Open Datasets | Yes | For the latter [real data], we use the New York taxi data set [NYC-Open Data, 2018]. [NYC-Open Data, 2018] NYC-Open Data. 2018 yellow taxi trip data. https://data.cityofnewyork.us/Transportation/ 2018-Yellow-Taxi-Trip-Data/t29m-gskq, 2018. Accessed: 2020-04-01. |
| Dataset Splits | No | The paper mentions using synthetic data and the New York taxi dataset, but it does not specify any training, validation, or test splits by percentages or sample counts, nor does it refer to predefined standard splits for reproducibility. |
| Hardware Specification | No | The paper mentions 'parallel computation with 16 cores' for runtime experiments but does not provide specific details such as CPU/GPU models, memory specifications, or types of computing infrastructure (e.g., cloud instances, workstations) used for the experiments. |
| Software Dependencies | No | The paper mentions that 'more than 99% of the computation time is spent constructing CPLEX LP objects' but does not provide a specific version number for CPLEX or any other software dependency used in the experiments. |
| Experiment Setup | Yes | We generate random road networks of 4 degrees maximum and average results over 32 simulations for each setting... We vary the taxi cost α and choose these loosely based on prices from London taxis. If we normalize the fuel cost to be β = 1, then α = 5 is considered a moderate value and α = 1 is cheap. As for the value of time, we set γi = γmax i/N to simulate heterogeneous riders... For other parameters we use K = N/2, T = 15, V = 10, α = 5, β = 1. |