کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9669413 | 868880 | 2005 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Development of a parallel optimization method based on genetic simulated annealing algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Development of a parallel optimization method based on genetic simulated annealing algorithm Development of a parallel optimization method based on genetic simulated annealing algorithm](/preview/png/9669413.png)
چکیده انگلیسی
This paper presents a parallel genetic simulated annealing (PGSA) algorithm that has been developed and applied to optimize continuous problems. In PGSA, the entire population is divided into sub-populations, and in each sub-population the algorithm uses the local search ability of simulated annealing after crossover and mutation. The best individuals of each sub-population are migrated to neighboring ones after a certain number of epochs. An implementation of the algorithm is discussed and the performance is evaluated against a standard set of test functions. PGSA shows some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Parallel Computing - Volume 31, Issues 8â9, AugustâSeptember 2005, Pages 839-857
Journal: Parallel Computing - Volume 31, Issues 8â9, AugustâSeptember 2005, Pages 839-857
نویسندگان
Z.G. Wang, Y.S. Wong, M. Rahman,