کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6855164 | 1437608 | 2018 | 43 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design
ترجمه فارسی عنوان
بهبود عملکرد آموزش بهینه سازی مبتنی بر یادگیری برای طراحی طرح ریزی ماشین
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کلمات کلیدی
هوش محاسباتی، بهینه سازی آموزش مبتنی بر یادگیری، طرح تسهیلات، طراحی قوی، تقاضای پویا،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various optimisation problems. However, TLBO has not been academically reported for solving the robust machine layout design (MLD) problems with dynamic demand. Considering internal logistics activities, shortening material flow distance within a manufacturing area can lead to efficient productivity and a decrease in related costs. The robust machine layout is concerned with determining the efficient arrangement of machines/facilities located on a manufacturing shop floor under future demand fluctuation. A robust designed layout is essential for a company to maintain a high productivity rate through multiple time-periods of demand uncertainty with minimum effects related to the re-layout time and cost, manufacturing disruption, and the movement of monument machines. The objectives of this paper were to: i) describe the development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario, ii) investigate the appropriate setting of TLBO parameters, and iii) propose four TLBO modifications for improving its performance. The modified TLBOs were inspired by multiple teachers with two types of classes and two approaches to teacher selection. The numerical experiments were designed and conducted using eleven MLD benchmarking datasets. Statistical analyses on the experimental results showed a superior performance for the proposed modifications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 98, 15 May 2018, Pages 129-152
Journal: Expert Systems with Applications - Volume 98, 15 May 2018, Pages 129-152
نویسندگان
Srisatja Vitayasak, Pupong Pongcharoen,