Bi-criteria appointment scheduling of patients with heterogeneous service sequences

This article addresses the challenges of scheduling patients with stochastic service times and heterogeneous service sequences in multi-stage facilities, while considering the availability and compatibility of resources with presence of a variety of patient types. The proposed method departs from existing literature by optimizing the scheduling of patients by integrating mathematical programming, simulation, and multiobjective tabu search methods to achieve our bi-objectives of minimizing the waiting time of patients and the completion time of the facility. Through intensive testing, the performance of the proposed approach is analyzed in terms of the solution quality and computation time, and is compared with the performance of the well-known method, Non-Dominated Sorting Genetic Algorithm (NSGA-II). The proposed method is then applied to actual data of a case study operating department in a major Canadian hospital and promising results have been observed. Based on this study, insights are provided for practitioners.