6533b82efe1ef96bd1293cf1
RESEARCH PRODUCT
Combining workload balance and patient priority maximisation in operating room planning through hierarchical multi-objective optimisation
Roberto AringhieriSimona ManciniSimona ManciniDavide DumaDavide DumaPaolo Landasubject
Class (computer programming)Information Systems and ManagementGeneral Computer ScienceOperations researchExploitbusiness.industryComputer sciencemedia_common.quotation_subjectMatheuristics Operating room planning and scheduling OR in health servicesOperating room planning and schedulingOperating room managementWorkloadManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringScheduling (computing)Quantitative analysis (finance)Modeling and SimulationMatheuristicsMatheuristics; Operating room planning and scheduling; OR in health servicesQuality (business)Local search (optimization)OR in health servicesSettore MAT/09 - Ricerca Operativabusinessmedia_commondescription
Abstract Previous analysis suggested the opportunity to consider the preferences of different stakeholders (hospital, patients, doctors and nurses) through the adoption of both patient priority maximisation and workload balance as performance criteria. The aim of this paper is to develop an effective and efficient solution approach for the operating room planning and scheduling capable to take into account the patient priority maximisation and workload balance criteria at the same time. This work is inspired by the need of a deeper understanding of the quality of the solutions obtained when a combination of the two criteria leads the OR planning decisions. Starting from a hierarchical multi-objective optimisation model for the combined master surgical scheduling and surgical cases assignment problems, we develop a class of new multi-neighbourhood local search based matheuristic algorithms, whose main feature is to exploit an ad hoc neighbourhood to generate better solutions in a significant shorter running time. A broad quantitative analysis on new realistic instances proves the effectiveness and the efficiency of the proposed matheuristic algorithms as well as to evaluate the quality of the computed solution from an operating room management perspective.
year | journal | country | edition | language |
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2022-04-16 |