Reducing patient-flow delays in surgical suites through determining start-times of surgical cases

Lee, Sangbok; Yih, Yuehwern

doi:10.1016/j.ejor.2014.03.043

Cited by 53 publications

(26 citation statements)

References 28 publications

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“…In addition, their methodology only addresses homogenous sequence of services and does not support multiple sequences. Lee and Yih (2014) proposed a simulation-based optimization method to schedule surgery cases in surgical suits. They developed a multiobjective method to minimize patients' wait time, idealness of resources, and completion time of the schedules.…”

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

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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

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“…The completion time of the whole physical examination scheduling is greater than or equal to the completion time of each physical examination scheduling, and each scheduling time is more than 0, which can be expressed by constraint (18) and (19).…”

Section: Jqhementioning

confidence: 99%

“…Su et al [18] regarded the problem of determining the optimal operating room schedule as a FJSP and proposed a SOMO-based approach for solving the operating room scheduling problem. Lee et al [19] studied the problem of completing multiple processes within one day as a flexible job shop model with fuzzy sets and proposed a scheduling strategy to determine the start time of multiple operating rooms. Behmanesh et al [20] researched the surgical case scheduling problem in multioperating theater environment with uncertain service times in order to minimize makespan and structured the no-wait multiresources fuzzy fexible job shop scheduling in operating theater.…”

Section: Introductionmentioning

confidence: 99%

An imperialist competition algorithm using a global search strategy for physical examination scheduling

Zhang²,

Duan

2020

Appl Intell

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The outbreak of the novel coronavirus clearly highlights the importance of the need of effective physical examination scheduling. As treatment times for patients are uncertain, this remains a strongly NP-hard problem. Therefore, we introduce a complex flexible job shop scheduling model. In the process of physical examination for suspected patients, the physical examiner is considered a job, and the physical examination item and equipment correspond to an operation and a machine, respectively. We incorporate the processing time of the patient during the physical examination, the transportation time between equipment, and the setup time of the patient. A unique scheduling algorithm, called imperialist competition algorithm with global search strategy (ICA GS) is developed for solving the physical examination scheduling problem. A local search strategy is embedded into ICA GS for enhancing the searching behaviors, and a global search strategy is investigated to prevent falling into local optimality. Finally, the proposed algorithm is tested by simulating the execution of the physical examination scheduling processes, which verify that the proposed algorithm can better solve the physical examination scheduling problem.

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“…For the surgical duration uncertainty, some researches considered stochastic surgical durations. Lee and Yih [25] incorporated fuzzy time duration in the flow shop model with restraint of beds in the unit Post-Anesthesia Care Unit. A genetic algorithm was proposed to solve the model.…”

Section: Literature Reviewmentioning

confidence: 99%

Multiple Due Time Surgical Scheduling With Truncated Learning and Deteriorating Effect

Song¹,

Zhang²,

Zhu³

2019

IEEE Access

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The surgical scheduling problem that incorporates the surgical duration, the setup time, the turnover time and the due time is studied in this paper. The actual surgical duration is affected by the normal duration, the surgical sequence, the accumulated experience of surgical teams and a controlling parameter. Besides, the surgical duration, the setup time and the turnover time are affected by the deteriorating effect, which means when the start time, the setup time or the turnover time of a surgery is postponed, the actual duration, the actual setup time or the actual turnover time will be prolonged. A schedule problem is formulated to minimize the maximum surgical tardiness. By building and analyzing the surgical scheduling model, each surgical team should operate surgeries according to a non-decreasing order of patients' normal surgical duration. Furthermore, a branch-and-bound algorithm is provided to solve the surgical teams scheduling problem. Our experimental results show the effectiveness and stability of our proposed algorithm. INDEX TERMS Deteriorating effect, surgical scheduling, truncated learning effect, various due times.

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Reducing patient-flow delays in surgical suites through determining start-times of surgical cases

Cited by 53 publications

References 28 publications

Bi-criteria appointment scheduling of patients with heterogeneous service sequences

Bi-criteria appointment scheduling of patients with heterogeneous service sequences

An imperialist competition algorithm using a global search strategy for physical examination scheduling

Multiple Due Time Surgical Scheduling With Truncated Learning and Deteriorating Effect

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