A hybrid Hill-ABC algorithm for patient admission scheduling problem

Abstract

The patient admission scheduling (PAS) problem is a well-known combinatorial optimization problem that entails the allocation of patients to some restricted bedspace for a certain period while adhering to a set of established constraints such as medical preferences and prerequisites. The existing algorithmic techniques utilized in solving the formulation of the PAS could not efficiently navigate the deep solution space due to the highly constrained nature of the formulation. Therefore, to address the drawbacks exhibited by the existing search methodologies when applied to the PAS problem, this paper proposed a solution template that hybridized the artificial bee colony (ABC) with hill climbing heuristic (HCH) named the Hill-ABC algorithm. Hill climbing is integrated within the operator of employed bees of the ABC algorithm to exploit the PAS’s rugged solution space and strike the right balance between diversification and intensification during search activities. The design of the proposed Hill-ABC approach is in two phases: The first phase is aimed at generating initial feasible solutions using a room selection-based method (RSM). Similarly, the second phase employed three neighbourhood structures to improve the quality of previously generated initial solutions. The proposed hybrid Hill-ABC algorithm is validated using the PAS standard datasets. The experiment analysis shows that the proposed method achieved better-quality solutions than most of the existing state-of-the-art algorithms.

Keywords

• Patient admission scheduling
• Swarm intelligence
• Hybrid metaheuristics
• Artificial bee colony
• Local search