300. ILP based approaches for a Chemotherapy Appointment Scheduling Problem
Contributed abstract in session MC-5: (Multi)Appointment /1, stream Regular talks.
Monday, 11:00-12:30Room: Room S6
Authors (first author is the speaker)
| 1. | Giuliana Carello
|
| Elettronica, Informazione e Bioingegneria, Politecnico di Milano | |
| 2. | Mauro Passacantando
|
| Department of Business and Law, University of Milano-Bicocca | |
| 3. | Elena Tanfani
|
| Department of Economics and Business Studies, University of Genova |
Abstract
The number of patients affected by cancer is expected to significantly increase in the next years, and the need for chemotherapy treatments will increase accordingly. This poses a great challenge: resources devoted to cancer treatments (medical and nursing staff, consultation rooms, seats and beds for the drug infusion) must be carefully managed to meet the increasing demand. In cancer centers, resources are shared among different specialties or pathologies, and hematological and oncological patients with different pathologies are jointly treated. This can improve the timeliness and quality of the cure, provided that resources and activities are carefully managed. The management of shared cancer centres involves different decision levels. In this work, we mainly focus on the chemotherapy multi-appointment scheduling problem, namely the problem of determining the day and starting time of the visit and infusion of the scheduled patients, which arises at the operational level. We consider different metrics related to patients' perspective and we formulate the problem as a multiobjective optimization problem tackled by sequentially solving three problems, in a lexicographic multi-objective fashion. We propose MILP based approaches to solve the three problems. The approaches are tested on real data from an Italian hospital.
Keywords
- (Multi) appointment scheduling
Status: accepted
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