The contemporary challenge of population aging in many societies necessitates innovative solutions for providing efficient and cost-effective healthcare services, particularly for elderly and terminally ill patients, such as those in the end stages of cancer. This research introduces a two-objective mathematical model designed for a one-day planning horizon to enhance patient satisfaction while concurrently reducing healthcare system costs. This study evaluates optimal solutions by implementing the model on various test problems using the ϵ-constraint method, Multi-Objective Adaptive Large Neighborhood Search (MOALNS), and Non-dominated Sorting Genetic Algorithm II (NSGA-II). Moreover, for large-scale test problems, the efficacy of the meta-heuristic approaches is validated. Results indicate that the MOALNS outperforms the NSGA-II algorithm in terms of Pareto solutions diversity and execution time. The set of non-dominated solutions obtained from this study holds significant value for home care centers, particularly benefiting institutions such as the Iranian Cancer Prevention and Control Center.
Shirneshan et al. (Tue,) studied this question.