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首页> 外文期刊>Evolutionary computation >Extending the “Open-Closed Principle” to Automated Algorithm Configuration
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Extending the “Open-Closed Principle” to Automated Algorithm Configuration

机译：将“开闭原理”扩展到自动算法配置

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摘要

Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of a metaheuristic for a given problem has historically been a manually intensive process based on experience, experimentation, and reasoning by metaphor. More recently, there has been interest in automating the process of algorithm configuration. In this article, we identify shared state as an inhibitor of progress for such automation. To solve this problem, we introduce the Automated Open-Closed Principle (AOCP), which stipulates design requirements for unintrusive reuse of algorithm frameworks and automated assembly of algorithms from an extensible palette of components. We demonstrate how the AOCP enables a greater degree of automation than previously possible via an example implementation.
机译：元启发法是一类有效且多样化的优化算法：一种针对其他棘手问题获得可接受质量的解决方案的方法。过去，针对给定问题的元启发式方法的选择，构建和配置一直是基于经验，实验和隐喻推理的手动密集过程。最近，人们对自动化算法配置过程感兴趣。在本文中，我们将共享状态确定为此类自动化进度的阻碍。为了解决此问题，我们引入了自动开闭原理（AOCP），该规范规定了对算法框架进行非侵入式重用以及从可扩展的组件面板中自动组装算法的设计要求。我们通过一个示例实现演示了AOCP如何实现比以前更高的自动化程度。

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