A patient flow scheduling problem in ophthalmology clinic solved by the hybrid EDA–VNS algorithm

This paper studies the patient flow scheduling problem in a multi-phase-multi-server system setting for a typical ophthalmology clinic, considering different patient flow processes and specific appointment time. In this problem, patients may go through the following processes, i.e., consultation, examination, re-consultation, and treatment, which form four patient flow paths according to different situations. The objective of this paper is to minimize the completion time of all the patients in the ophthalmology clinic. For solving this problem, we develop a hybrid meta-heuristic algorithm EDA–VNS combining estimation of distribution algorithm (EDA) and variable neighborhood search (VNS). We test the suitability of the approach for the ophthalmology clinic’s problem. Computational results demonstrate that the proposed algorithm is capable of providing high-quality solutions within a reasonable computational time. In addition, the proposed algorithm is also compared with several high-performing algorithms to validate its efficiency. The results indicate the advantages of the proposed EDA–VNS algorithm.