我们考虑的问题最小化一个连续可微的函数的几个变量服从　　简单数据绑定约束限制的一些变量的整数值。我们假设　　目标函数的一阶衍生品可以显式计算和近似。　　这类混合整数非线性优化问题出现在许多工业和频繁　　科学应用,这促使derivative-free方法的研究越来越感兴趣　　他们的解决方案。连续变量是由linesearch策略而解决　　离散的我们雇佣当地的一个类型的搜索方法。我们提出了不同的算法　　以当前迭代的方式更新和满意的平稳性条件　　序列的极限点。-We consider the problem of minimizing a continuously differentiable function of several variables subject to

simple bound constraints where some of the variables are restricted to take integer values. We assume that

the first order derivatives of the objective function can be neither calculated nor approximated explicitly.

This class of mixed integer nonlinear optimization problems arises frequently in many industrial and

scientific applications and this motivates the increasing interest in the study of derivative-free methods

for their solution. The continuous variables are handled by a linesearch strategy whereas to tackle

the discrete ones we employ a local search-type approach. We propose different algorithms which are

characterized by the way the current iterate is updated and by the stationarity conditions satisfied by the

limit points of the sequences they produce.