Simple Rules for Low-Knowledge Algorithm Selection
Simple Rules for Low-Knowledge Algorithm Selection
复制标题
低知识算法选择的简单规则
DOI：
10.1007/978-3-540-24664-0_4
复制
发表时间：
2004
影响因子：
6.3
通讯作者：
Eugene C. Freuder
中科院分区：
文献类型：
--
作者：
J. Christopher Beck;Eugene C. Freuder
本文讨论了从预定义集合中选择一种算法的问题，该算法将在调度问题实例上具有最佳性能。我们的目标是减少应用约束技术所需的专业知识。因此，我们研究简单的规则，使预测的基础上有限的问题实例知识。我们的研究结果表明，它是可能的，以实现上级的性能超过选择的算法，表现最好的平均问题集。结果保持在各种不同的运行长度和不同类型的调度问题和算法。我们认为，低知识的方法是重要的，在减少所需的专业知识，利用优化技术。
This paper addresses the question of selecting an algorithm from a predefined set that will have the best performance on a scheduling problem instance. Our goal is to reduce the expertise needed to apply constraint technology. Therefore, we investigate simple rules that make predictions based on limited problem instance knowledge. Our results indicate that it is possible to achieve superior performance over choosing the algorithm that performs best on average on the problem set. The results hold over a variety of different run lengths and on different types of scheduling problems and algorithms. We argue that low-knowledge approaches are important in reducing expertise required to exploit optimization technology.