混合变量问题的一种全局优化方法的实现
On the implementation of a global optimization method for mixed-variable problems
摘要：
我们描述了在开源的无导数求解器RBFOpt中实现的优化算法。该算法基于Gutmann的径向基函数方法和Regis和Shoemaker的度量随机响应面方法。我们提出了几个修改，旨在推广和改进这两个算法：（i）使用一个扩展的空间来表示一元编码的分类变量;（ii）一个细化阶段，局部改善候选解决方案;（iii）插值模型没有unisolvence条件，既帮助处理分类变量，并启动优化之前，唯一确定的模型是可能的;（iv）允许并行地进行异步目标函数评估的主工作者框架。数值实验表明了这些思想的有效性。
英文摘要：
We describe the optimization algorithm implemented in the open-source derivative-free solver RBFOpt. The algorithm is based on the radial basis function method of Gutmann and the metric stochastic response surface method of Regis and Shoemaker. We propose several modifications aimed at generalizing and improving these two algorithms: (i) the use of an extended space to represent categorical variables in unary encoding; (ii) a refinement phase to locally improve a candidate solution; (iii) interpolation models without the unisolvence condition, to both help deal with categorical variables, and initiate the optimization before a uniquely determined model is possible; (iv) a master-worker framework to allow asynchronous objective function evaluations in parallel. Numerical experiments show the effectiveness of these ideas.
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