دانلود مقاله ISI انگلیسی شماره 78518
عنوان فارسی مقاله

یک مدل برنامه نویسی آرمانی برای ساکنان برنامه ریزی در بخش بیهوشی و احیا

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
78518 2013 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A goal programming model for scheduling residents in an anesthesia and reanimation department
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 40, Issue 6, May 2013, Pages 2117–2126

کلمات کلیدی
پزشک مقیم - برنامه ریزی تغییر؛ بیهوشی و احیا؛ برنامه ریزی آرمانی؛ فرایند سلسله مراتبی تحلیلی
پیش نمایش مقاله
پیش نمایش مقاله یک مدل برنامه نویسی آرمانی برای ساکنان برنامه ریزی در بخش بیهوشی و احیا

چکیده انگلیسی

Medicine residency is three to seven years of challenging graduate medical training that puts a lot of mental and physiological burden over the residents. Like other surgical branches, anesthesia and reanimation departments provide 24 h continuous service and the residents are the main providers of this service. The residents are assigned for on-call shifts during their training, as well as working during the regular day shifts. These schedules must address several considerations like preferences of the residents and coverage requirements of two different locations: the intensive care unit (ICU) and the surgery room (SR). In this study we develop a goal programming (GP) model for scheduling the shifts of the residents in the Anesthesia and Reanimation Department of Bezmialem Vakif University Medical School (BUMS). The rules that must be strictly met, like the number of on-duty shifts or preventing block shifts, are formulated as hard constraints. The preferences of the residents like increasing the number of weekends without shifts and assigning duties on the same night to the same social groups are formulated as soft constraints. The penalties for the deviation from the soft constraints are determined by the analytical hierarchy process (AHP). We are able to solve problems of realistic size to optimality in a few seconds. We showed that the proposed formulation, which the department uses currently, has yielded substantial improvements and much better schedules are created with less effort.

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