论文标题
全球非线性整数优化的增强填充功能
An augmented filled function for global nonlinear integer optimization
论文作者
论文摘要
在许多实际问题领域中，发现非线性离散功能的全球最小值的问题。近年来，基于离散填充功能的方法随着解决此类问题的方式而流行。但是，他们依靠最陡峭的下降方法进行本地搜索。在这里，我们提出了一种不取决于特定局部优化方法的方法，以及具有有用属性的新离散填充函数，该属性是一种良好的连续全局优化算法应用于IT的算法会导致非线性离散问题解决方案的近似值。给出数值结果，显示了新方法的效率。
The problem of finding global minima of nonlinear discrete functions arises in many fields of practical matters. In recent years, methods based on discrete filled functions become popular as ways of solving these sort of problems. However, they rely on the steepest descent method for local searches. Here we present an approach that does not depend on a particular local optimization method, and a new discrete filled function with the useful property that a good continuous global optimization algorithm applied to it leads to an approximation of the solution of the nonlinear discrete problem. Numerical results are given showing the efficiency of the new approach.
