Simulation optimization in healthcare resource planning: A literature review

AbstractAbstractIn healthcare, the planning and the management of resources are challenging as there are always many complex and stochastic factors in both demand and supply. Simulation Optimization (SO) that combines simulation analysis and optimization techniques is well suited for solving complicated, stochastic, and mathematically intractable decision problems. In order to comprehensively unveil the degree to which SO has been used to solve healthcare resource planning problems, this article reviews the academic articles published until 2021 and categorizes them into multiple classification fields that are related to either problem perspectives (i.e., healthcare services, planning decisions, and objectives) or methodology perspectives (i.e., SO approaches and applications). We also examine the relations between the individual fields. We find that emergency care services are the most applied domain of SO, and that discrete-event simulation and random search methods (especially genetic algorithms) are the most frequently used methods. The literature classification can help researchers quickly learn this research area and identify the publications of interest. Finally, we identify major trends, insights and conclusions that deserve special attention when studying this area. We suggest many avenues for further research that provide opportunities for expanding existing methodologies and for narrowing the gap between theory and practice.Keywords: Healthcare managementsimulation optimizationoperations managementresource capacity planningliterature review AcknowledgmentsThe authors thank the department editor, the anonymous associate editor, and the anonymous referees for their constructive comments that have significantly improved this paper.Additional informationFundingThis work was supported by the China Scholarship Council (No.201806890017). We would like to acknowledge the China Scholarship Council for the financial support to the first author.Notes on contributorsLien WangLien Wang obtained his PhD degree from the Research Center for Operations Management in the Department of Decision Sciences and Information Management at KU Leuven. His research interests include simulation modeling and analysis, simulation optimization, decision making and optimization under uncertainty as well as their applications to healthcare systems.Erik DemeulemeesterErik Demeulemeester is Professor in the Research Center for Operations Management and currently Chair of the Department of Decision Sciences and Management Informatics at the Faculty of Economics and Business Studies at KU Leuven. He is Full Professor from 2001 on and teaches a course on project and production scheduling, a PhD course on combinatorial optimization and local search techniques as well as a seminar on operations management. His main research interests are situated in the field of project scheduling and health care (operating room) planning and he has published many papers on these and related topics. He is one of the coordinators of the EURO Working Group on Project Management and Scheduling.