زمان‌بندی گردش شغلی درون و برون سلول‌های ناب با رویکرد الگوریتم بهینه‌سازی مبتنی بر آموزش و یادگیری

نوع مقاله: مقاله پژوهشی

نویسنده

استادیار، گروه مدیریت کسب‌وکار، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

چکیده

سیستم‌های سرو در زمره پیشرفته‌ترین سیستم‌های تولید  تکراری به شمار می‌روند که در حجم کم یا متوسط تولید می‌کنند. این سیستم‌ها متشکل از چندین سلول بوده و از طریق روش‌های نوین تخصیص متصدی ها، به بهترین زمان جریان کار دست می‌یابند. تحقیقات انجام‌شده در این حوزه بیشتر به جنبه‌های شکل‌گیری، تخصیص و توالی محصولات مختلف به سلول‌ها توجه کرده‌اند و موضوع تخصیص متصدی ها  که بااهمیت‌ترین عنصر در این سیستم‌ها به‌حساب می‌آیند، همسنگ با دیگر تصمیمات موردمطالعه قرار نگرفته است؛ لذا در این مقاله این تصمیمات به‌طور مستقل بررسی و در قالب گردش شغلی درون و بین سلول‌ها تحلیل شده است. مدل ارائه‌شده، یک مدل برنامه‌ریزی خطی عدد صحیح (ILP) است که مجموعه‌ای از متصدی را به سلول‌ها تخصیص می‌دهد؛ به‌نحوی‌که عدم جابجایی‌های بین سلولی در دوره‌های متوالی کمینه شود. برای حل مدل، از نرم‌افزار گمز استفاده شده و همچنین به‌منظور بهبود کارایی حل برای مسائل با ابعاد متوسط و بزرگ، الگوریتم ابتکاری بهینه‌سازی مبتنی بر آموزش و یادگیری طراحی شده است. چندین مسئله نمونه در ابعاد مختلف برای بررسی اعتبار مدل و عملکرد الگوریتم به‌صورت تصادفی ایجاد و حل شده‌اند که حاکی از کارایی و کیفیت مناسب این الگوریتم است.

کلیدواژه‌ها


عنوان مقاله [English]

Intra- and inter-Serus job rotation scheduling through Teaching and Learning Based Optimization approach

نویسنده [English]

  • ashkan ayough
MANAGEMENT FACULTY, SHAHID BEHESHTI UNIVERSITY, TEHRAN
چکیده [English]

Seru systems are among the most advanced repetitive manufacturing systems which produce in low or medium volumes.   These systems consist of several cells and get the best flow time through the new methods of assigning operators. In the literature, more attention is paid to the aspects of the cells formation and allocation and sequencing of the various products into the cells, and the assignment of operators, which is considered to be the most important element in these systems, has not been studied in line with other decisions. Therefore, in this paper, these decisions have been studied independently and analyzed through intra and inter serus job rotation scheduling. The presented ILP model assigns a given set of operators to the cells so that the total number of stays in a cell in successive rotation periods be minimized. GAMS software has been used to solve the model and also, the teaching and learning based optimization algorithm has been designed to improve the efficiency for problems of medium and large sizes. Several test problems have been generated and solved in a variety of sizes to examine the validity of the model and the performance of the algorithm. Results show the proper efficiency of the algorithm and quality of its solutions.

کلیدواژه‌ها [English]

  • Seru production system
  • job rotation
  • Integer linear programming (ILP)
  • Teaching and Learning Based Optimization (TLBO)
  • GAMS
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