a hybrid approach for home health care routing and scheduling using an agent-based model

Home health care systems, as a growing economic system in the field of health systems, face various problems and issues such as routing, scheduling and allocation. given that a growing number of home health care workers in health care systems around the world tend to work for themselves instead of hospitals or other health care institutions. as a result, centralized and one-factor models are not responsible for solving these problems. therefore, this paper focuses on situations by designing an agent-based planning system that is simulated in a decentralized environment and using the fuzzy c-means clustering algorithm and the repetitive suggestion mechanism (vickery) as a negotiation protocol focuses on situations that a home health care agency needs to schedule a home visit among a group of independent physicians. the goal of the home health care agency is to minimize the overall cost of the service by covering all patients by qualified physicians. the results of the implementation of the proposed algorithm for real geographical data in the city of tehran in gams show that this framework achieves a high efficiency of optimal solutions.