کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
493994 723184 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new cuckoo search algorithm for 2-machine robotic cell scheduling problem with sequence-dependent setup times
ترجمه فارسی عنوان
یک الگوریتم جستجوی فاخته جدید برای مشکل برنامه ریزی سلول رباتیک ماشین 2 همراه با زمان نصب وابسته به توالی
کلمات کلیدی
برنامه ریزی با زمان نصب وابسته به توالی؛ سلول رباتیک تمرکزیافته ماشین 2 ؛ چرخه های تک واحدی ؛ زمان چرخه کل ؛ الگوریتم جستجوی فاخته؛ حداقل توالی بخشی از مجموعه ؛ ترتیب و توالی حرکت ربات
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

The paper addresses the problem of 2-machine robotic cell scheduling of one-unit cycle with sequence-dependent setup times and different loading/unloading times of the parts. As an alternative metaheuristic algorithm, the cuckoo search algorithm has recently attracted growing interests of researchers. It has the capability to search globally as well as locally to converge to the global optimality by exploring the search space more efficiently due to its global random walk governed by Levy flights, rather than standard isotropic random walk. In this study, a discrete cuckoo search algorithm is proposed to determine the sequence of robot moves along with the sequence of parts so that the cycle time is minimized. In the proposed algorithm, the fractional scaling factor based procedure is presented to determine the step length of Levy flights distribution in discrete from and then, using this step length, two neighborhood search techniques, interchange and cyclical shift methods are applied to the current solution to obtain improved solution. A response surface methodology based on desirability function is used to enhance the convergence speed of the proposed algorithm. Also, a design of experiment is employed to tune the operating parameters of the algorithm. Finally, empirical results with a large number of randomly generated problem instances involving large part sizes varying from 200 to 500 under different operating conditions are compared with two well-known algorithms in the literature and demonstrate the effectiveness of the proposed algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Swarm and Evolutionary Computation - Volume 28, June 2016, Pages 131–143
نویسندگان
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