并行优化中的新挑战

E. Alba
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引用次数: 0

摘要

并行和优化是在许多应用程序中一起使用的两个学科。在优化中解决复杂的问题往往意味着要面对复杂的搜索场景,这需要耗时的操作。精确和启发式技术现在被用来解决数学、物流、生物信息学、电信和许多其他相关领域的问题。对于这些任务,在许多情况下必须处理集群计算、多处理器甚至计算网格。在这次演讲中,我将讨论使用并行工具、软件和硬件扩展现有优化过程以在并行环境中工作的基本挑战。我将介绍一些基本的优化算法,特别是启发式算法,并讨论并行性在它们中的应用。此外,我将展示由于并行性而产生的新技术如何成为可能,从而产生全新的算法和新的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Challenges in Parallel Optimization
Parallelism and Optimization are two disciplines that are used together in numerous applications. Solving complex problems in optimization often means to face complex search landscapes, what needs time-consuming operations. Exact and heuristic techniques are being used nowadays to get solutions to problems in mathematics, logistics, bioinformatics, telecommunications, and many other relevant fields. For these tasks it is mandatory to deal with cluster computing in many cases, multiprocessors, and even with computational grids. In this talk I will address the basic challenges of using parallel tools, software, and hardware for extending existing optimization procedures to work in a parallel environment. I will present some basic optimization algorithms, especially heuristic ones, and discuss the application of parallelism to them. Also, I will show how new techniques become possible due to parallelism, giving birth to a whole new class of algorithms and new research lines.
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