Joint Optimization of Service Routing and Scheduling in Home Health Care

TL;DR

This paper presents a novel integrated optimization model for home health care that combines routing and scheduling, incorporating uncertainty to improve efficiency and service quality.

Contribution

It introduces a stochastic VRASP model and a VNS heuristic, advancing operational decision-making in home health care services.

Findings

Stochastic model outperforms deterministic in cost and quality.

VNS heuristic finds near-optimal solutions efficiently.

Scalable approach for large-scale home health care routing.

Abstract

The growing aging population has significantly increased demand for efficient home health care (HHC) services. This study introduces a Vehicle Routing and Appointment Scheduling Problem (VRASP) to simultaneously optimize caregiver routes and appointment times, minimizing costs while improving service quality. We first develop a deterministic VRASP model and then extend it to a stochastic version using sample average approximation to account for travel and service time uncertainty. A tailored Variable Neighborhood Search (VNS) heuristic is proposed, combining regret-based insertion and Tabu Search to efficiently solve both problem variants. Computational experiments show that the stochastic model outperforms the deterministic approach, while VNS achieves near-optimal solutions for small instances and demonstrates superior scalability for larger problems compared to CPLEX. This work provides HHC providers with a practical decision-making tool to enhance operational efficiency under uncertainty.