کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
425126 685689 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improved auto control ant colony optimization using lazy ant approach for grid scheduling problem
ترجمه فارسی عنوان
کنترل خودکار بهبودیافته بهینه سازی کلونی مورچه با استفاده از روش مورچه تنبل برای مسئله برنامه ریزی شبکه
کلمات کلیدی
بهینه سازی مورچه Colony به صورت اتوماتیک (AACO)؛ مسئله برنامه ریزی شبکه (GSP)؛ الگوریتم ژنتیک کوانتومی (QGA)؛ شبیه سازی آنیل (SA)؛ بهینه سازی ازدحام ذرات (PSO)
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی


• This work proposes an improvement in auto controlled ant colony optimization method for grid scheduling problem.
• Auto Control mechanism dynamically adapts changes in GSP through the ant.
• The concept of Lazy Ants has been introduced, which fully exploits the solution around the best ant.
• The algorithm is effective in producing better result as well as efficient in computational time over some contemporary ACO, PSO, GA, QGA and AACO for GSP.

An auto controlled ant colony optimization algorithm controls the behavior of the ant colony algorithm automatically based on a priori heuristic. During the experimental study of auto controlled ACO algorithm on grid scheduling problem, it was observed that the induction of lazy ants not only reduces the time complexity of the algorithm but also produces better results on the given objectives. Lazy ants are basically a mutated version of active ants that remain alive till the fitter lazy ants are generated in the successive generations. This work presents an improved auto controlled ACO algorithm using the lazy ant concept. Performance study reveals the efficacy and the efficiency achieved by the proposed algorithm. A comparative study of the proposed method with some other recent meta-heuristics such as auto controlled ant colony optimization algorithm, genetic algorithm, quantum genetic algorithm, simulated annealing and particle swarm optimization for grid scheduling problem exhibits so.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volume 60, July 2016, Pages 78–89
نویسندگان
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