RSCS: A parallel simplex algorithm for the nimrod/O optimization toolset

被引：0
|
作者：
Lewis, A [1 ]
Abramson, D [1 ]
Peachey, T [1 ]
机构：
[1] Griffith Univ, Div Informat Serv, Brisbane, Qld 4111, Australia
来源：
ISPDC 2004: THIRD INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING/HETEROPAR '04: THIRD INTERNATIONAL WORKSHOP ON ALGORITHMS, MODELS AND TOOLS FOR PARALLEL COMPUTING ON HETEROGENEOUS NETWORKS, PROCEEDINGS | 2004年
关键词：
parallel programming; optimization; Nelder-Mead algorithm;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper describes a method of parallelisation of the popular Nelder-Mead simplex optimization algorithms that can lead to enhanced performance on parallel and distributed computing resources. A reducing set of simplex vertices are used to derive search directions generally closely aligned with the local gradient. When tested on a range of problems drawn from real-world applications in science and engineering 7, this reducing set concurrent simplex (RSCS) variant of the Nelder-Mead algorithm compared favourably with the original algorithm, and also with the inherently parallel multidirectional search algorithm (MDS). All algorithms were implemented and tested in a general-purpose, grid-enabled optimization toolset.
引用
收藏
页码：71 / 78
页数：8
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