A MULTI-OBJECTIVE APPROACH TO HOME HEALTH CARE ROUTING PROBLEM WITH TEAM FORMATION

Authors

  • Gulcin Bektur Department of Industrial and Systems Engineering, The University of Iowa, Iowa City, United States | Department of Industrial Engineering Iskenderun Technical University Hatay, Turkey
  • David Nembhard Department of Engineering, Harvey Mudd College California, United States

DOI:

https://doi.org/10.23055/ijietap.2023.30.5.8737

Abstract

Home health care (HHC) services provide the elderly, disabled, and those with chronic diseases health services in their homes. The demand for HHC services has increased due to the growth of the elderly population, the increase in hospital occupancy rates during the pandemic, and developments in medical device technologies. In this study, team formation is taken into consideration in a multi-period and multi-objective HHC assignment, scheduling and routing problem. The team and the assigned patients to this team must be compatible with skill levels and operational requirements. The objective functions are minimization of total completion time and maximum working time overall caregivers. To evaluate our approach, an HHC service unit in a state hospital is adopted as the operational scenario, and we propose a multi-objective mathematical model to solve the problem. In this model, HHC teams are formed, the patients are assigned to the teams, and the route of each team is determined in an integrated manner. The variable neighborhood search algorithm is modified to solve the multi-objective optimization model and is improved with a local search algorithm. The proposed algorithm has been compared with the state-of-the-art multi-objective algorithms in the literature over test problems. Current results show that the model to be an effective means of estimating and predicting system behavior in this complex environment.

Published

2023-10-17

How to Cite

Bektur, G., & Nembhard, D. (2023). A MULTI-OBJECTIVE APPROACH TO HOME HEALTH CARE ROUTING PROBLEM WITH TEAM FORMATION. International Journal of Industrial Engineering: Theory, Applications and Practice, 30(5). https://doi.org/10.23055/ijietap.2023.30.5.8737

Issue

Section

Operations Research