کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
433065 689225 2012 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A parallel and distributed meta-heuristic framework based on partially ordered knowledge sharing
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
A parallel and distributed meta-heuristic framework based on partially ordered knowledge sharing
چکیده انگلیسی

We propose a new distributed and parallel meta-heuristic framework to address the issues of scalability and robustness in the optimization problem. The proposed framework, named PADO (Parallel And Distributed Optimization framework), can utilize heterogeneous computing and communication resources to achieve scalable speedup while maintaining high solution quality. Specifically, we combine an existing meta-heuristic framework with a loosely coupled distributed island model for scalable parallelization. Based on a mature sequential optimization framework, we implement a population-based meta-heuristic algorithm with an island model for parallelization. The coordination overhead of previous approaches is significantly reduced by using a partially ordered knowledge sharing (POKS) model as an underlying model for distributed computing. The resulting framework can encompass many meta-heuristic algorithms and can solve a wide variety of problems with minimal configuration. We demonstrate the applicability and the performance of the framework with a traveling salesman problem (TSP), multi-objective design space exploration (DSE) problem of an embedded multimedia system, and a drug scheduling problem of cancer chemotherapy.


► We propose a new distributed and parallel meta-heuristic framework.
► Scalable speedup can be achieved by using the partially ordered knowledge sharing.
► Many meta-heuristic algorithms and a wide range of problems can be configured easily.
► The case studies demonstrate the applicability of our framework.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 72, Issue 4, April 2012, Pages 564–578
نویسندگان
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