Approximately Stable Pricing for Coordinated Purchasing of Electricity
Authors: Andrew Perrault, Craig Boutilier
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical results show these schemes achieve a high degree of stability in practice and can be made more stable by sacrificing small amounts (< 2%) of social welfare. |
| Researcher Affiliation | Collaboration | Andrew Perrault and Craig Boutilier Department of Computer Science University of Toronto {perrault, cebly}@cs.toronto.edu Currently on leave at Google, Inc., Mountain View. |
| Pseudocode | No | The paper describes procedures in prose but does not include any formal pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement about releasing source code or a link to a code repository for its methodology. |
| Open Datasets | Yes | We use a model of the US residential energy market. Building characteristics are based on the 2011 Buildings Energy Data Book [D&R International, Ltd., 2012]. |
| Dataset Splits | No | The paper mentions running '50 trials for each experiment' and using '50 consumers, 2 producers, 4 profiles per consumer, 24 time periods', but it does not specify explicit training, validation, or test dataset splits. |
| Hardware Specification | Yes | We are able to solve instances with 5000 consumers, 2 producers, 4 profiles and 24 time periods in less than 15 minutes on a 12x2.6GHz, 32GB machine using CPLEX 12.51. |
| Software Dependencies | Yes | We are able to solve instances with 5000 consumers, 2 producers, 4 profiles and 24 time periods in less than 15 minutes on a 12x2.6GHz, 32GB machine using CPLEX 12.51. |
| Experiment Setup | Yes | In all experiments, we use 50 consumers, 2 producers, 4 profiles per consumer, 24 time periods, and run 50 trials for each experiment. We sample 30 random join orders, a number which was determined empirically to induce convergence. |