The Gamma-Robustness paradigm, by Bertsimas and Sim, has been extensively applied due to the good trade-off between offered level of robustness and computational tractability. This is true, in particular, in network application contexts where the service provided to the final users is a critical issue, and therefore the uncertainty which usually characterizes some user parameters should be carefully taken into account.
In this seminar, after an overview on the classical Gamma-Robustness approach, some Gamma-Robustness extensions which have been recently proposed in the literature in order to capture specific problem characteristics, and/or peculiar uncertainty structures, will be presented.
Then, the use of Gamma-Robustness extensions will be illustrated in a Health Care application context, where uncertainty in user requests may be particularly critical: the Home Care problem under uncertain demands.
The Home Care application addresses several aspects involved in planning home care services, such as the scheduling of patient requests over a multiple-day time horizon, the caregiver-to-patient assignment, and the caregiver routing. In this context, cancellation of requests and additional demand for known or new patients are very frequent. Thus, managing user demand uncertainty is of paramount importance in limiting service disruptions that might occur when such events realize. The uncertainty of patient demands is addressed via a non-standard Gamma-Robustness approach, by jointly considering assignment, scheduling and routing decisions. The results of a wide experimentation on robust instances generated starting from a publicly available data set, and comprising real world Home Care instances, are reported. Future avenues of research are discussed.
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