Appointment scheduling of outpatient surgical services in a multistage operating room department

Saremi, Alireza; Jula, Payman; ElMekkawy, Tarek Y.; Wang, G. Gary

doi:10.1016/j.ijpe.2012.10.004

Cited by 101 publications

(61 citation statements)

References 95 publications

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“…Building on the insights by Gul et al (2011) that merely combining simulation and heuristics may not necessarily provide the most promising results, they reported that incorporation of mathematical programming significantly improves the performance of simulation-based optimization methods. However, similar to several other articles tackling multiobjective scheduling of patients, Saremi et al (2013) and Gul et al (2011) did not offer a Pareto front of solutions. Rather, they only provided a single solution for each scenario.…”

Section: Literature Reviewmentioning

confidence: 60%

“…More recently, Saremi, Jula, ElMekkawy, and Wang (2013) proposed a novel simulation-based optimization method by incorporating mathematical programming to schedule day surgeries. Building on the insights by Gul et al (2011) that merely combining simulation and heuristics may not necessarily provide the most promising results, they reported that incorporation of mathematical programming significantly improves the performance of simulation-based optimization methods.…”

Section: Literature Reviewmentioning

confidence: 99%

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Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Saremi

Jula

ElMekkawy

et al. 2015

Expert Systems with Applications

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Section: Literature Reviewmentioning

confidence: 60%

Section: Literature Reviewmentioning

confidence: 99%

Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Saremi

Jula

ElMekkawy

et al. 2015

Expert Systems with Applications

Self Cite

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“…In this way, users not familiar with optimization theories can also apply our tool to schedule patients. The approach to scheduling patients proposed in this paper is different from those reported in [19,22,23,24].…”

Section: Resultsmentioning

confidence: 86%

Scheduling Patients in Hospitals Based on Multi-agent Systems

Hsieh

Lin

2014

Modern Advances in Applied Intelligence

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Abstract. Scheduling patients in a hospital is a challenging issue as it calls for a sustainable architecture and an effective scheduling scheme that can dynamically schedule the available resources. The objectives of this paper are to propose a viable and systematic approach to develop a distributed cooperative problem solver for scheduling patients based on MAS to minimize the patient stay in a hospital. Our solution approach combines contract net protocol (CNP), multi-agent system architecture, process specification model based on time Petri net (TPN) and optimization theories. Our system first automatically formulate patient scheduling problem based on the TPN models. The patient scheduling problem is decomposed into a number of subproblems that are solved by cooperative agents. A collaborative algorithm is invoked by individual agents to optimize the schedules locally based on a problem formulation automatically obtained by the Petri net models. To realize our solution methodology, we proposed a scheme for publication and discovery of agents' services based on FIPA compliant multi-agent system platform. We develop a scheduling system to solve the dynamic patient scheduling problem.

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“…In addition, three simulation-based optimization methods have been proposed to minimize patients' completion time, the patients' waiting time, and the number of surgery cancellations. Some comments on the applications of the proposed models and methods are also provided [15]. To resolve the OR scheduling problem, multiple real-life constraints are included in the model using the constraint-programming paradigm.…”

Section: Introductionmentioning

confidence: 99%

Clinical Pathways Scheduling Using Hybrid Genetic Algorithm

Jiang

Yang

et al. 2013

J Med Syst

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In order to improve the standard of management in hospitals and effectively control the cost of clinical treatments, this research primarily focuses on optimizing the scheduling of clinical pathways (CPs). A mathematical model for CP scheduling is constructed, and the hybrid genetic algorithm (HGA, combining a genetic algorithm with particle swarm optimization) is proposed for solving this problem so as to distribute medical resources and schedule the treatments of patients reasonably and effectively. The optimal search space can be further enlarged by introducing a new mutation mechanism, which allows a more satisfactory solution to be found. In particular, the relative patient waiting time and relative time efficiency are used as measure indexes, which are more scientific and effective than the usual indexes of absolute time and absolute time efficiency. After comparing absolute waiting time, relative waiting time, utilization of absolute waiting time, and utilization of relative waiting time waiting respectively, the conclusion can confidently be drawn that task scheduling obviously enhances patients' time efficiency, reduces time wastage and therefore promotes patient satisfaction with medical processes. Moreover, the patients can to a certain degree move away from their usual passive role in medical processes by using this scheduling system. In order to further validate the rationality and validity of the proposed method, the heuristic rules for CP scheduling are also tested using the same case. The results demonstrate that the proposed HGA achieves superior performance, in terms of precision, over those heuristic rules for CP scheduling. Therefore, we utilize HGA to optimize CP scheduling, thus providing a decision-making mechanism for medical staff and enhancing the efficiency of medical processes. This research has both theoretical and practical significance for electronic CP management, in particular.

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Appointment scheduling of outpatient surgical services in a multistage operating room department

Cited by 101 publications

References 95 publications

Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Scheduling Patients in Hospitals Based on Multi-agent Systems

Clinical Pathways Scheduling Using Hybrid Genetic Algorithm

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