کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7563036 1491532 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Self-adaptive multi-objective teaching-learning-based optimization and its application in ethylene cracking furnace operation optimization
ترجمه فارسی عنوان
بهینه سازی آموزش مبتنی بر یادگیری چند هدفه ای خود سازگار و کاربرد آن در بهینه سازی عملیات کوره اتیلن کراکینگ
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
A self-adaptive multi-objective teaching-learning-based optimization (SA-MTLBO) is proposed in this paper. In SA-MTLBO, the learners can self-adaptively select the modes of learning according to their levels of knowledge in classroom. The excellent learners are more likely to choose the learner phase to enhance population diversity, and the common learners are tend to choose the teacher phase to improve the convergence ability of the algorithm. So learners at different levels choose appropriate modes of learning and carry out corresponding search function to efficiently enhance the performance of algorithm. To evaluate the effectiveness of the proposed algorithm, SA-MTLBO is firstly compared with other algorithms in twelve test problems. The results demonstrate that SA-MTLBO can generate Pareto optimal fronts with good convergence and distribution. Finally, SA-MTLBO is used to maximize the yields of ethylene, propylene, and butadiene of the naphtha pyrolysis process. The computational results of SA-MTLBO indicate that the operation of ethylene cracking furnace can be improved by increasing the yields of ethylene, propylene, and butadiene.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 146, 15 August 2015, Pages 198-210
نویسندگان
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