Trust regions in Kriging-based optimization with expected improvement
Trust regions in Kriging-based optimization with expected improvement
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DOI：
10.1080/0305215x.2015.1082350
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发表时间：
2016-06
影响因子：
2.7
通讯作者：
R. Regis
中科院分区：
文献类型：
--
作者：
R. Regis
基于Kriging的高效全局优化（EGO）方法可以很好地解决许多昂贵的黑盒优化问题。然而，它似乎并没有表现出良好的问题与陡峭和狭窄的全球最小盆地和高维问题。本文开发了一种新的基于Kriging的优化方法，称为TRIKE（Trust Region Implementation in Kriging-based optimization with Expected improvement），该方法实现了一种类似于信任域的方法，其中通过最大化某个信任域内的预期改进（EI）函数来获得每个目标。根据实际改进与EI的比率来调整该信赖区域。本文还开发了基于Kriging的CYCLONE（CYCLIC Local search in OptimizatioN using Expected improvement）方法，该方法使用循环模式来确定EI最大化的搜索区域。TRIKE和CYCLONE与EGO在多达32个维度的28个测试问题上进行了比较，并在附录中的36维地下水生物修复应用中进行了比较，附录作为在线补充提供，可在http://dx.doi.org/10.1080/0305215X.2015.1082350上获得。结果表明，这两种算法都产生了显着的改善，他们是有竞争力的径向基函数方法。
The Kriging-based Efficient Global Optimization (EGO) method works well on many expensive black-box optimization problems. However, it does not seem to perform well on problems with steep and narrow global minimum basins and on high-dimensional problems. This article develops a new Kriging-based optimization method called TRIKE (Trust Region Implementation in Kriging-based optimization with Expected improvement) that implements a trust-region-like approach where each iterate is obtained by maximizing an Expected Improvement (EI) function within some trust region. This trust region is adjusted depending on the ratio of the actual improvement to the EI. This article also develops the Kriging-based CYCLONE (CYClic Local search in OptimizatioN using Expected improvement) method that uses a cyclic pattern to determine the search regions where the EI is maximized. TRIKE and CYCLONE are compared with EGO on 28 test problems with up to 32 dimensions and on a 36-dimensional groundwater bioremediation application in appendices supplied as an online supplement available at http://dx.doi.org/10.1080/0305215X.2015.1082350. The results show that both algorithms yield substantial improvements over EGO and they are competitive with a radial basis function method.