Surgical cases assignment problem using an efficient genetic programming hyper-heuristic

Abstract

The surgical case assignment problem (SCAP) is vital to the operating room planning problem. Although several methods have been applied, the solution accuracy can be improved further. In this paper, an efficient genetic programming hyper-heuristic (GP-HH) algorithm is proposed for the SCAP to minimize the total operating cost. First, eight simple and adaptive heuristic rules are devised to constitute a set of low-level heuristics (LLHs). Second, genetic programming is employed as a high-level heuristic to dynamically manage LLHs applied to the solution domain. Third, effective solution encoding and the corresponding decoding schemes are developed to represent individuals and construct valid schedules. To investigate the influence of parameter settings, we performed a design-of-experiment (DOE). The effectiveness of GP-HH is executed on a typical benchmark dataset. The experimental results demonstrate the superiority of the proposed GP-HH scheme over existing approaches.