Stochastic optimization problems with nondifferentiable cost functionals with an application in stochastic programming
Stochastic optimization problems with nondifferentiable cost functionals with an application in stochastic programming
复制标题
具有不可微成本函数的随机优化问题及其在随机规划中的应用
DOI：
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发表时间：
1972
期刊：
影响因子：
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通讯作者：
D. Bertsekas
中科院分区：
文献类型：
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作者：
D. Bertsekas
本文研究了一类目标函数不可微的随机优化问题。它表明，在许多情况下，目标函数的期望值是可微的，从而产生的优化问题可以分析和解决，使用经典的解析或数值方法。结果随后被应用到解决一类随机规划问题。
In this paper we examine a class of stochastic optimization problems characterized by nondifferentiability of the objective function. It is shown that in many cases the expected value of the objective function is differentiable and thus the resulting optimization problem can be analyzed and solved by using classical analytical or numerical methods. The results are subsequently applied to the solution of a class of stochastic programming problems.