Short-Term Scientific Mission

Robust Randomized Search Heuristics for Healthcare Logistics Under Uncertainty

Main theme: Optimisation Under Uncertainty
Grantee: Soumen Atta, University of Jyväskylä, Jyväskylä, Finland
Host: Yingjie Fan, LIACS, Leiden University, Leiden, Netherlands

Start date: 2025-08-25
End date: 2025-09-12
Awarded: 2025-05-02
Report approved: 2025-10-31

Description

The goal of this STSM is to design and evaluate robust randomized search heuristics for solving healthcare logistics problems under uncertainty. The plan is to collaborate with experts at LIACS to address challenges in healthcare routing, scheduling, and facility location. Activities include problem modeling, algorithm development, and preliminary benchmarking. The work will explore adaptive and robust randomization strategies and contribute to ROAR-NET themes such as optimization under uncertainty and benchmarking.

Achievements

The STSM successfully defined and modeled a novel Stochastic Home Healthcare Location–Routing–Scheduling Problem with Flexible Depots, Caregiver Skills, and Soft Time Windows as a two-stage stochastic MILP. A tailored stochastic integer L-shaped decomposition approach was developed, and discussions explored the integration of randomized metaheuristics. Classical location-routing benchmark instances were adapted to generate preliminary datasets for experimentation, with plans to release the final dataset publicly. Collaborative exchanges with LIACS researchers advanced methodological understanding in stochastic optimization and healthcare logistics. The STSM laid the foundation for joint publications, open benchmarking resources, and long-term collaborative research aligned with ROAR-NET objectives.