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3227. Models and solution approaches for the consistent vehicle routing problem under stochastic travel and service times
Invited abstract in session MA-35: Robust and Stochastic Routing Problems, stream Stochastic, Robust and Distributionally Robust Optimization.
Monday, 8:30-10:00Room: 44 (building: 303A)
Authors (first author is the speaker)
| 1. | Yossiri Adulyasak
|
| Gestion des Opérations et de la Logistique, HEC Montréal | |
| 2. | Seyede Saeede Hosseini
|
| Polytechnique Montreal | |
| 3. | Louis-Martin Rousseau
|
| Mathematic and Industrial Engineering, École Polytechnique de Montréal |
Abstract
We explore a consistent vehicle routing problem for home health care under uncertain travel and service times. In this problem, the planner must schedule and route a group of care workers to visit patients multiple times over a planning horizon while ensuring service consistency so that each patient will be serviced by the same care worker at the same time slot every time the service is provided. This problem variant extends the home health care routing and scheduling problem (HHCRSP) to include service level constraints under stochastic travel and service times. We propose a stochastic solution framework where the uncertainty is represented by (i) a discrete scenario set and (ii) an extreme value theory-based (EVT-based) approximation. A unified branch-and-check algorithm that leverages constraint programming (CP) to handle the subproblem is developed to efficiently solve the stochastic models with these uncertainty representations. Results show that the stochastic optimization framework can efficiently handle practical benchmark instances and produce schedules with significantly improved service levels than the deterministic model.
Keywords
- Stochastic Optimization
- Vehicle Routing
- Scheduling
Status: accepted
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