Comparison of selection rules for ordinal optimization
Comparison of selection rules for ordinal optimization
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DOI：
10.1016/j.mcm.2005.05.032
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发表时间：
2006-05
期刊：
影响因子：
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通讯作者：
Q. Jia;Y. Ho;Qianchuan Zhao
中科院分区：
文献类型：
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作者：
Q. Jia;Y. Ho;Qianchuan Zhao
通过仿真对复杂离散事件系统的设计进行性能评估通常是非常耗时的。优化系统性能在计算上变得更加不可行的。序数优化（OO）是一种用于解决系统设计中的这一困难的技术，它着眼于设计中性能的“顺序”而不是“价值”，并为足够好的解决方案提供概率保证，而不是最好的解决方案。选择规则，即决定选择哪个设计子集作为OO解决方案的规则，是应用OO方法的关键步骤。两两淘汰和循环比较是两个选择规则的例子。在序数优化文献中也经常使用许多其他选择规则。为了比较选择规则，我们首先确定一些关于选择规则的一般事实。然后，我们使用回归函数来量化一组选择规则的效率，包括一些经常使用的规则。提出了一种预测良好选择规则的方法，并通过仿真和实例验证了该方法的正确性。推荐在大多数情况下工作良好的选择规则。
The evaluation of performance of a design for complex discrete event systems through simulation is usually very time consuming. Optimizing the system performance becomes even more computationally infeasible. Ordinal optimization (OO) is a technique introduced to attack this difficulty in system design by looking at “order” in performances among designs instead of “value” and providing a probability guarantee for a good enough solution instead of the best for sure. The selection rule, known as the rule to decide which subset of designs to select as the OO solution, is a key step in applying the OO method. Pairwise elimination and round robin comparison are two selection rule examples. Many other selection rules are also frequently used in the ordinal optimization literature. To compare selection rules, we first identify some general facts about selection rules. Then we use regression functions to quantify the efficiency of a group of selection rules, including some frequently used rules. A procedure to predict good selection rules is proposed and verified by simulation and by examples. Selection rules that work well most of the time are recommended.