دانلود مقاله ISI انگلیسی شماره 52434
ترجمه فارسی عنوان مقاله

نرم افزار هوش مصنوعی برای بهینه سازی برنامه ریزی زمانی کمپرسور

عنوان انگلیسی
Applications of artificial intelligence for optimization of compressor scheduling
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
52434 2006 14 صفحه PDF
منبع

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

Journal : Engineering Applications of Artificial Intelligence, Volume 19, Issue 2, March 2006, Pages 113–126

ترجمه کلمات کلیدی
الگوریتم های ژنتیکی؛ شبکه های عصبی؛ برنامه ریزی زمانی کمپرسور
کلمات کلیدی انگلیسی
Genetic algorithms; Neural networks; Compressor scheduling
پیش نمایش مقاله
پیش نمایش مقاله  نرم افزار هوش مصنوعی برای بهینه سازی برنامه ریزی زمانی کمپرسور

چکیده انگلیسی

This paper presents a feasibility study of evolutionary scheduling for gas pipeline operations. The problem is complex because of several constraints that must be taken into consideration during the optimization process. The objective of gas pipeline operations is to transfer sufficient gas from gas stations to consumers so as to satisfy customer demand with minimum costs. The scheduling involves selection of a set of compressors to operate during a shift. The scheduling decision has to be made so as to satisfy the dual objectives of minimizing the sum of fuel cost, start-up cost, the cost of gas wasted due to oversupply, and satisfying minimal operative and inoperative time of the compressors. The problem was decomposed into the two subproblems of gas load forecast and selection of compressors. Neural networks were used for forecasting the load; and genetic algorithms were used to search for a near optimal combination of compressors. The study was conducted on a subsystem of the pipeline network located in southeastern Saskatchewan, Canada. The results are compared with the solutions generated by an expert system and a fuzzy linear programming model.