An Effective Iterated Greedy Algorithm for Elective Surgery Scheduling Problem

This paper aims to provide a solution method for the elective surgery scheduling problem with the goal of minimizing makespan, which has important application in hospital. We first introduce a surgery process based on a comprehensive investigation. Then we propose an effective iterative greedy (IG)algorithm with the permutation-based representation and based on the problem-specific characteristics. The proposed IG algorithm incorporates the heuristic and improvement procedures including a hybrid operator and slack model-based acceleration evolution. Finally, we generate instances according to real-world statistical data and evaluate the proposed IG algorithm with other state-of-the-art IG algorithm by designed for the similar problem. The results show that the proposed IG algorithm is more effective than other algorithm after comprehensive computational comparisons and statistical analysis.