摘要翻译：
空军卫星控制网(AFSCN)调度这一特殊的超额预订调度应用程序的最佳性能算法似乎没有什么共同点。然而，通过在实际问题实例中对性能进行仔细的实验和建模，我们可以将最佳算法的特性与应用程序的特性联系起来。特别是，我们发现平台控制搜索空间（因此有利于对解进行较大变化的算法），并且搜索中的一些随机化对良好的性能至关重要（由于缺乏平台上的梯度信息）。在解释算法性能的基础上，我们提出了一种新的算法，该算法结合了性能最好的算法的特点；新算法的性能比以前最好的算法要好。我们展示了假设驱动的实验和搜索建模是如何解释算法性能和激励新算法设计的。
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英文标题：
《Understanding Algorithm Performance on an Oversubscribed Scheduling
  Application》
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作者：
L. Barbulescu, A. E. Howe, M. Roberts, L. D. Whitley
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithms performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm.
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PDF链接：
https://arxiv.org/pdf/1110.2735