A Location-Allocation-Routing Model for a Home Health Care Supply Chain Problem
Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar
Abstract:
With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.
Keywords: Home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1316245
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1055References:
[1] Atashpaz-Gargari, E., & Lucas, C. (2007, September). Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In Evolutionary computation, 2007. CEC 2007. IEEE Congress on (pp. 4661-4667). IEEE.
[2] Braekers, K., Hartl, R. F., Parragh, S. N., & Tricoire, F. (2016). A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience. European Journal of Operational Research, 248(2), 428-443.
[3] Fikar, C., & Hirsch, P. (2015). A matheuristic for routing real-world home service transport systems facilitating walking. Journal of Cleaner Production, 105, 300-310.
[4] Fikar, C., & Hirsch, P. (2017). Home health care routing and scheduling: A review. Computers & Operations Research, 77, 86-95.
[5] Fathollahi Fard, A. M., Gholian-Jouybari, F., Paydar M. M. & Hajiaghaei-Keshteli, M., (2017). A Bi-objective Stochastic Closed-loop Supply Chain Network Design Problem Considering Downside Risk. Industrial Engineering and Management System, 16, (3), 342-362.
[6] Harris, M. D. (2015). Handbook of home health care administration. Jones & Bartlett Publishers.
[7] Golshahi-Roudbaneh, A., Hajiaghaei-Keshteli, M., & Paydar, M. M. (2017). Developing a lower bound and strong heuristics for a truck scheduling problem in a cross-docking center. Knowledge-Based Systems, 129, 17-38.
[8] Hiermann, G., Prandtstetter, M., Rendl, A., Puchinger, J., & Raidl, G. R. (2015). Metaheuristics for solving a multimodal home-healthcare scheduling problem. Central European Journal of Operations Research, 23(1), 89-113.
[9] Sadeghi-Moghaddam, S., Hajiaghaei-Keshteli, M., & Mahmoodjanloo, M. (2017). New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment. Neural Computing and Applications, 1-21.
[10] Shi, Y., Boudouh, T., & Grunder, O. (2017). A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand. Expert Systems with Applications, 72, 160-176.
[11] Fathollahi Fard, A. M., & Hajiaghaei-Keshteli, M., (2018). A tri-level location-allocation model for forward/reverse supply chain. Applied Soft Computing, 62, 328-346.