A problem-based scenario reduction approach for stochastic chemotherapy planning
European Journal of Operational Research, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.ejor.2026.10.019
- Dergi Adı: European Journal of Operational Research
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Applied Science & Technology Source, Compendex, EconLit, INSPEC, MathSciNet, Public Affairs Index, zbMATH, Business Source Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Chemotherapy planning, OR in health services, Outpatient chemotherapy center, Scenario reduction, Stochastic programming
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
The rising global demand for chemotherapy, combined with the limited capacity of chemotherapy units, highlights the need for efficient treatment planning. We address the problem of assigning multiple treatments of each patient to specific days and chairs over a fixed planning horizon, while accounting for uncertainty in treatment durations. The model incorporates time window constraints and nurse workload limitations, and is formulated as a two-stage stochastic mixed-integer program. Deviations such as earliness, tardiness, within-window delays, deferrals to the next planning period, and overtime are penalized in the objective function. To address the computational burden of large scenario sets, we develop problem-based scenario reduction algorithms by extending a recent method from the stochastic programming literature. Using real data from an outpatient chemotherapy center, we evaluate our approach against alternative problem-based scenario reduction techniques and practical benchmark heuristics. To better reflect practice, we implement the approach within a rolling horizon framework. Finally, we perform sensitivity analyses and assess the value of stochastic solution.