coPSSA -约束平行拉伸模拟退火

J. Rufino, A. Pereira, J. Pidanic
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引用次数: 2

摘要

并行拉伸模拟退火(PSSA)通过将拉伸模拟退火优化方法并行应用于原始可行域的多个子域,解决了分布式存储集群中无约束的多局部规划优化问题。这项工作提出了coPSSA(约束并行拉伸模拟退火),这是一种混合应用程序,将基于共享内存的并行性与PSSA相结合,以有效地解决约束多局部规划问题。我们设计并评估了两种不同的并行策略来寻找这些问题的解决方案。一小部分测试问题的评估结果在解搜索时间上往往达到超线性加速,从而证明了coPSSA并行化方法的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
coPSSA - Constrained Parallel Stretched Simulated Annealing
Parallel Stretched Simulated Annealing (PSSA) solves unconstrained multilocal programming optimization problems in distributed memory clusters, by applying the Stretched Simulated Annealing optimization method, in parallel, to multiple sub-domains of the original feasible region. This work presents coPSSA (constrained Parallel Stretched Simulated Annealing), an hybrid application that combines shared memory based parallelism with PSSA, in order to efficiently solve constrained multilocal programming problems. We devise and evaluate two different parallel strategies for the search of solutions to these problems. Evaluation results from a small set of test problems often reach superlinear speedup in the solution search time, thus proving the merit of the coPSSA parallelization approach.
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