Discrete stochastic optimization using variants of the stochastic ruler method
Discrete stochastic optimization using variants of the stochastic ruler method
复制标题
使用随机标尺法变体的离散随机优化
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
S. Andradóttir
中科院分区：
文献类型：
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作者：
M. Alrefaei;S. Andradóttir
提出了求解离散随机优化问题的两种随机搜索方法。这两种方法都是随机标尺算法的变体。它们不同于我们之前对随机标尺算法的修改，因为它们使用不同的方法来估计最优解。我们的新方法保证在温和条件下几乎肯定地收敛于全局最优解集。讨论了在什么条件下这些新方法比改进的随机标尺算法收敛得更快。我们还讨论了如何使用这些方法来解决使用瞬态或稳态模拟估计目标函数值时的离散优化问题。最后，我们给出了数值结果，将我们的新方法与改进的随机标尺算法在解决缓冲区分配问题时的性能进行了比较。©2005 Wiley期刊公司海军研究后勤，2005。
We present two random search methods for solving discrete stochastic optimization problems. Both of these methods are variants of the stochastic ruler algorithm. They differ from our earlier modification of the stochastic ruler algorithm in that they use different approaches for estimating the optimal solution. Our new methods are guaranteed to converge almost surely to the set of global optimal solutions under mild conditions. We discuss under what conditions these new methods are expected to converge faster than the modified stochastic ruler algorithm. We also discuss how these methods can be used for solving discrete optimization problems when the values of the objective function are estimated using either transient or steady‐state simulation. Finally, we present numerical results that compare the performance of our new methods with that of the modified stochastic ruler algorithm when applied to solve buffer allocation problems. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.