کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4951111 | 1364326 | 2016 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Novel parallelization of simulated annealing and Hooke & Jeeves search algorithms for multicore systems with application to complex fisheries stock assessment models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
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چکیده انگلیسی
Estimating parameters of a statistical fisheries assessment model typically involves a comparison of disparate datasets to a forward simulation model through a likelihood function. In all but trivial cases the estimations of these models tend to be time-consuming due to issues related to multi-modality and non-linearity. This paper develops novel parallel implementations of popular search algorithms, applicable to expensive function calls typically encountered in fisheries stock assessment. It proposes two versions of both Simulated Annealing and Hooke & Jeeves optimization algorithms with the aim of fully utilizing the processing power of common multicore systems. The proposals have been tested on a 24-core server using three different input models. Results indicate that the parallel versions are able to take advantage of available resources without sacrificing the quality of the solution.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational Science - Volume 17, Part 3, November 2016, Pages 599-608
Journal: Journal of Computational Science - Volume 17, Part 3, November 2016, Pages 599-608
نویسندگان
Sergio Vázquez, MarÃa J. MartÃn, Basilio B. Fraguela, Andrés Gómez, Aurelio RodrÃguez, Bjarki Ãór Elvarsson,