Title: Computer simulation and swarm intelligence organisation into an emergency department: a balancing approach across Ant Colony Optimisation

Authors: Fabio Fruggiero, Alfredo Lambiase, Daithi Fallon

Addresses: Department of Mechanical Engineering, University of Salerno, Via Ponte Don Melillo 1, 84084 Fisciano, SA, Italy. ' Department of Mechanical Engineering, University of Salerno, Via Ponte Don Melillo 1, 84084 Fisciano, SA, Italy. ' Department of Manufacturing, Biomedical & Facilities Engineering, Cork Institute of Technology (CIT), Rossa Avenue, Bishopstown, Cork, Ireland

Abstract: Healthcare system must be sensitive to the needs of patient, financially viable and cost-effective. Emergency Department (ED) crowding and rising healthcare costs are perceived as significant issues that are getting worse. In order to respond to the growing number of incoming patients, hospital departments, including emergency rooms, have to re-evaluate their current facilities, procedures and practises from an operations management perspective. In a typical ED, it is important to minimise not only the patient|s waiting time but also the staff idle time while maintaining the high utilisation rate of medical facilities. Computer simulation is recognised as a powerful tool, for medical management, to enquire productivity trying to increase service level to patients. Based on the analogy of a Job Shop Scheduling Problem (JSSP) and known patient scheduling methodologies, a metaheuristic Swarm Intelligence (SI) approach, focused on Ant System (AS) behaviour, was used in the balancing of an ED. The Ant Colony Optimisation (ACO) algorithm was implemented with the proposal to optimise patient scheduling under defined precedence, zoning and capacity constraints while balancing the workload between and within resource types. The ED of Cork University Hospital (CUH), Ireland, is the case in issue.

Keywords: healthcare management; emergency departments; computer simulation; line balancing; swarm intelligence; ant systems; ant colony optimisation; ACO; hospital departments; operations management; medical management; job shop scheduling; patient scheduling.

DOI: 10.1504/IJSOI.2008.019330

International Journal of Services Operations and Informatics, 2008 Vol.3 No.2, pp.142-161

Available online: 07 Jul 2008

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