دانلود مقاله ISI انگلیسی شماره 105606
ترجمه فارسی عنوان مقاله

الگوریتم فراشناختی ترکیبی برای بهینه سازی یک سلول رباتیک در دنیای واقعی

عنوان انگلیسی
A hybrid metaheuristic algorithm to optimise a real-world robotic cell
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
105606 2017 19 صفحه PDF
منبع

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

Journal : Computers & Operations Research, Volume 84, August 2017, Pages 188-194

ترجمه کلمات کلیدی
سلول روبوتیک، ربات ثابت، ربات موبایل، جدول زمانبندی کار، حمل و نقل رباتیک، متهوریستی،
کلمات کلیدی انگلیسی
Robotic cell; Stationary robot; Mobile robot; Job shop scheduling; Robotic transportation; Metaheuristics;
پیش نمایش مقاله
پیش نمایش مقاله  الگوریتم فراشناختی ترکیبی برای بهینه سازی یک سلول رباتیک در دنیای واقعی

چکیده انگلیسی

In this paper, a real-world robotic cell is investigated by transforming it into a special job shop with a set of stationary robots for manufacturing the parts of a product (i.e., operations of a job) at multiple operational stages. In addition, this robotic cell contains a particular mobile robot to transport the parts among stationary robots inside the cell as well as a depot (for initialising the production) and a stockpile (for stocking the complete products) outside the cell. Thus, a new scheduling problem called Blocking Job Shop Scheduling problem with Robotic Transportation (BJSSRT) is proposed. A numerical example is presented to illustrate the characteristics and complexity of BJSSRT. According to the problem properties, four types of robotic movements are defined for a mobile robot in an operation’s execution: processing-purpose, depot-purpose, return-purpose and stocking-purpose. By satisfying complex feasibility conditions, an innovative graph-based constructive algorithm is developed to produce a good feasible BJSSRT schedule. Embedded with the constructive algorithm, a hybrid Tabu Search and Threshold Accepting metaheuristic algorithm is developed to find a near-optimal solution in an efficient way. The proposed BJSSRT methodology has practical benefits in modelling the automated production system using stationary and mobile robots, especially in manufacturing and mining industries.