Tackling Large-Scale Home Health Care Delivery Problem with Uncertainty

Authors

  • Cen Chen Singapore Management University
  • Zachary Rubinstein Carnegie Mellon University
  • Stephen Smith Carnegie Mellon University
  • Hoong Chuin Lau Singapore Management University

DOI:

https://doi.org/10.1609/icaps.v27i1.13845

Abstract

In this work, we investigate a multi-period Home Health Care Scheduling Problem (HHCSP) under stochastic service and travel times. We first model the deterministic problem as an integer linear programming model that incorporates real-world requirements, such as time windows, continuity of care, workload fairness, inter-visit temporal dependencies. We then extend the model to cope with uncertainty in durations, by introducing chance constraints into the formulation. We propose efficient solution approaches, which provide quantifiable near-optimal solutions and further handle the uncertainties by employing a sampling-based strategy. We demonstrate the effectiveness of our proposed approaches on instances synthetically generated by real-world dataset for both deterministic and stochastic scenarios.

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Published

2017-06-05

How to Cite

Chen, C., Rubinstein, Z., Smith, S., & Lau, H. C. (2017). Tackling Large-Scale Home Health Care Delivery Problem with Uncertainty. Proceedings of the International Conference on Automated Planning and Scheduling, 27(1), 358-366. https://doi.org/10.1609/icaps.v27i1.13845