دانلود مقاله ISI انگلیسی شماره 78446
ترجمه فارسی عنوان مقاله

احتمال مشترک برای ارزیابی برنامه زمان بندی و هزینه مدل های شبیه سازی تصادفی

عنوان انگلیسی
Joint probability for evaluating the schedule and cost of stochastic simulation models
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78446 2015 16 صفحه PDF
منبع

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

Journal : Advanced Engineering Informatics, Volume 29, Issue 3, August 2015, Pages 380–395

ترجمه کلمات کلیدی
شبیه سازی تصادفی؛ احتمال مشترک؛ احتمال تجمعی شرطی؛ برآورد احتمالی مشترک؛ نسل برنامه زمان بندی؛ تعداد دانه
کلمات کلیدی انگلیسی
Stochastic simulation; Joint probability; Conditional cumulative probability; Joint contingency estimation; Schedule generation; Seed number
پیش نمایش مقاله
پیش نمایش مقاله  احتمال مشترک برای ارزیابی برنامه زمان بندی و هزینه مدل های شبیه سازی تصادفی

چکیده انگلیسی

The review of construction engineering and management literature shows that the occurrence of multi-performance indices in stochastic simulation models have been treated the same way as the occurrence of a single performance index. By doing so, the correlation between these indices and the impact they have on each other are ignored. Their occurrences have been treated as disjoint, which leads to errors in evaluating the probabilities of the performance indices of these models. The objectives of this paper are to present a new method that can: (1) quantify the impact of uncertainty on the project schedule and cost simultaneously; (2) calculate the conditional probability of the project cost given a specific project duration, and vice versa; (3) find the best project duration and cost that meet a specific joint probability; (4) estimate the project schedule and cost joint contingency using joint probability; and (5) generate a schedule representing a specific joint probability. The paper presents the implementation details and several case studies to demonstrate the feasibility of the proposed method. The proposed method shall provide a more accurate analysis to the output of stochastic simulation.