Heuristic pattern search and its hybridization with simulated annealing for nonlinear global optimization
Heuristic pattern search and its hybridization with simulated annealing for nonlinear global optimization
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DOI：
10.1080/10556780310001645189
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发表时间：
2004-06
影响因子：
2.2
通讯作者：
A. Hedar;M. Fukushima
中科院分区：
文献类型：
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作者：
A. Hedar;M. Fukushima
在这篇文章中，我们提出了一种新的混合模拟退火方法来最小化多模型函数称为模拟退火启发式模式搜索（SAHPS）方法。提出了两种辅助方法来实现全局搜索方法SAHPS的最终形式。首先，我们介绍了近似下降方向（ADD）的方法，这是一个导数免费的过程，具有很高的能力产生下降方向。然后，将ADD方法与方向剪枝模式搜索方法相结合，构造了启发式模式搜索（HPS）方法。最后一种方法与模拟退火（SA）杂交，得到SAHPS方法。通过著名的测试函数的实验结果表明，所提出的方法SAHPS的效率。
In this article, we present a new approach of hybrid simulated annealing method for minimizing multimodel functions called the simulated annealing heuristic pattern search (SAHPS) method. Two subsidiary methods are proposed to achieve the final form of the global search method, SAHPS. First, we introduce the approximate descent direction (ADD) method, which is a derivative-free procedure with high ability of producing a descent direction. Then, the ADD method is combined with a pattern search method with direction pruning to construct the heuristic pattern search (HPS) method. The last method is hybridized with simulated annealing (SA) to obtain the SAHPS method. The experimental results through well-known test functions are shown to demonstrate the efficiency of the proposed method SAHPS.