دانلود مقاله ISI انگلیسی شماره 26131
ترجمه فارسی عنوان مقاله

یک روش برنامه نویسی چند هدفه تصادفی فازی-مقاوم برای برنامه ریزی مدیریت ضایعات نفتی

عنوان انگلیسی
A fuzzy-robust stochastic multiobjective programming approach for petroleum waste management planning
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
26131 2010 11 صفحه PDF
منبع

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

Journal : Applied Mathematical Modelling, Volume 34, Issue 10, October 2010, Pages 2778–2788

ترجمه کلمات کلیدی
برنامه نویسی چندمنظوره - تصادفی - فازی - مقاوم - مدیریت ضایعات نفت
کلمات کلیدی انگلیسی
Multiobjective programming, Stochastic,Fuzzy, Robust,Petroleum waste management
پیش نمایش مقاله
پیش نمایش مقاله  یک روش برنامه نویسی چند هدفه تصادفی فازی-مقاوم برای برنامه ریزی مدیریت ضایعات نفتی

This paper proposes a fuzzy-robust stochastic multiobjective programming (FRSMOP) approach, which integrates fuzzy-robust linear programming and stochastic linear programming into a general multiobjective programming framework. A chosen number of noninferior solutions can be generated for reflecting the decision-makers’ preferences and subjectivity. The FRSMOP method can effectively deal with the uncertainties in the parameters expressed as fuzzy membership functions and probability distribution. The robustness of the optimization processes and solutions can be significantly enhanced through dimensional enlargement of the fuzzy constraints. The developed FRSMOP was then applied to a case study of planning petroleum waste-flow-allocation options and managing the related activities in an integrated petroleum waste management system under uncertainty. Two objectives are considered: minimization of system cost and minimization of waste flows directly to landfill. Lower waste flows directly to landfill would lead to higher system costs due to high transportation and operational costs for recycling and incinerating facilities, while higher waste flows directly to landfill corresponding to lower system costs could not meet waste diversion objective environmentally. The results indicate that uncertainties and complexities can be effectively reflected, and useful information can be generated for providing decision support.