مشخصات مقاله | |
ترجمه عنوان مقاله | تجزیه و تحلیل مدل ها برای مشکل زمانبندی روش سرپایی تصادفی |
عنوان انگلیسی مقاله | Analysis of models for the Stochastic Outpatient Procedure Scheduling Problem |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 11 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
4.712 در سال 2018 |
شاخص H_index | 226 در سال 2019 |
شاخص SJR | 2.205 در سال 2018 |
شناسه ISSN | 0377-2217 |
شاخص Quartile (چارک) | Q1 در سال 2018 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | دارد |
رشته های مرتبط | پزشکی |
گرایش های مرتبط | بهداشت عمومی |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | مجله اروپایی درباره تحقیقات عملیاتی – European Journal of Operational Research |
دانشگاه | Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, United States |
کلمات کلیدی | OR در خدمات بهداشتی، زمانبندی معین، کلینیک های سرپایی، برنامه ریزی تصادفی، برنامه ریزی مخلوط عدد صحیح |
کلمات کلیدی انگلیسی | OR in health services، Appointment scheduling، Outpatient clinics، Stochastic programming، Mixed-integer programming |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ejor.2019.06.023 |
کد محصول | E13516 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract 1. Introduction 2. Literature review 3. Stochastic mixed-integer linear programming models of the SOPSP 4. Computational experiments 5. Conclusion Acknowledgments Appendix A. Comparison of linear programming relaxations of models (S) of (1) and (M) of (2) References |
بخشی از متن مقاله: |
Abstract
In this paper, we present a new stochastic mixed-integer linear programming model for the Stochastic Outpatient Procedure Scheduling Problem (SOPSP). In this problem, we schedule a day’s worth of procedures for a single provider, where each procedure has a known type and associated probability distribution of random duration. Our objective is to minimize the expectation of a weighted sum of patient waiting time, provider idling, and clinic overtime. We present computational results to show the size and characteristics of problem instances that can be solved with our model. We also compare this model to other formulations in the literature and analyze them both empirically and theoretically, demonstrating where significant improvements in performance can be gained with our proposed model. This work is motivated by our research on developing scheduling templates for endoscopic procedures at a major medical center. More broadly, however, the SOPSP is a stochastic single-resource sequencing and scheduling problem and therefore has applications both within and outside of healthcare operations. Introduction In this paper, we address the Stochastic Outpatient Procedure Scheduling Problem (SOPSP), which arises in outpatient procedure centers (OPCs). In this problem, we consider the perspective of an OPC manager who must schedule the start times for a day’s worth of procedures for a single provider, where each procedure has a known type and a random (non-negative) duration that follows a known probability distribution associated with the procedure type. Given the uncertainty in procedure durations, the goal is to minimize the expectation of a weighted sum of total patient waiting time (the time from the scheduled start of a procedure to its actual start), total provider idle time (the time from the end of one procedure to the start of the next), and clinic overtime (the time from the scheduled closing time of the clinic to the end of the last procedure of the day). This research is motivated by our work with the University of Michigan Medical Procedures Unit, an OPC that performs a variety of endoscopic procedures such as colonoscopies. The ultimate goal of this project is to optimize daily schedule templates and policies for filling these templates, to best account for variability in patient procedure times. By building higher-quality schedules that incorporate the variability in procedure durations, it is possible to ∗ Corresponding author. E-mail address: ksheha@umich.edu (K.S. Shehadeh). improve patient and provider satisfaction, reduce costs, and even achieve better clinical outcomes. A valuable tool in creating such templates is the ability to solve the simpler (and yet still challenging) SOPSP as an embedded sub-problem. |