READ ME File For "Fair Online Allocation of Perishable Goods and its Application to Electric Vehicle Charging"

Dataset DOI: 10.5258/SOTON/D0926

Creator: Alvaro Perez-Diaz, University of Southampton
Contact email: a.perez-diaz@soton.ac.uk


This dataset supports the publication:

E. Gerding, A. Perez-Diaz, H. Aziz, S. Gaspers, A. Marcu, N. Mattei, T. Walsh. "Fair Online Allocation of Perishable Goods and its Application to Electric Vehicle Charging", Proceedings of the 28th International Joint Conference on Artificial Intelligence (2019).


This dataset contains:

All data for the two different simulations presented in the paper: varying the number of agents (varyAgents) and varying the supply and keeping a fixed number of 45 agents (varySupply).

For each of the two scenarios, we present data for each algorithm and for the four different objectives discussed in the paper:
- Number of envious agents
- Envy quantity
- Max delivered
- Max satisfied

Algorithm names are specified in the header of each file.



Date of data collection: 02, 2019

Information about geographic location of data collection: University of Southampton, U.K.

Licence: CC BY

Date that the file was created: 05, 2019