@inproceedings{5f74a3f352404c12951c5aae84fb24c8,
title = "Mixed integer optimal compensation: Decompositions and mean-field approximations",
abstract = "Mixed integer optimal compensation deals with optimizing integer- and real-valued control variables to compensate disturbances in dynamic systems. The mixed integer nature of controls might be a cause of intractability for instances of larger dimensions. To tackle this issue, we propose a decomposition method which turns the original n-dimensional problem into n independent scalar problems of lot sizing form. Each scalar problem is then reformulated as a shortest path one and solved through linear programming over a receding horizon. This last reformulation step mirrors a standard procedure in mixed integer programming. We apply the decomposition method to a mean-field coupled multi-agent system problem, where each agent seeks to compensate a combination of the exogenous signal and the local state average. We discuss a large population mean-field type of approximation as well as the application of predictive control methods.",
author = "Dario Bauso and Quanyan Zhu and Tamer Basar",
year = "2012",
doi = "10.1109/acc.2012.6315277",
language = "English (US)",
isbn = "9781457710957",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2663--2668",
booktitle = "2012 American Control Conference, ACC 2012",
address = "United States",
note = "2012 American Control Conference, ACC 2012 ; Conference date: 27-06-2012 Through 29-06-2012",
}