The artificial bee colony (ABC) algorithm is a popular metaheuristic that was originally conceived for tackling continuous function optimization tasks. Over the last decade, a large number of variants of ABC have been proposed, making it by now a well-studied swarm intelligence algorithm. Typically, in a paper on algorithmic variants of ABC algorithms, one or at most two of its algorithmic components are modified. Possible changes include variations on the search equations, the selection of candidate solutions to be explored, or the adoption of features from other algorithmic techniques. In this article, we propose to follow a different direction and to build a generalized ABC algorithm, which we call ABC-X. ABC-X collects algorithmic components available from known ABC algorithms into a common algorithm framework that allows not only to instantiate known ABC variants but, more importantly, also many ABC algorithm variants that have never been explored before in the literature. Automatic algorithm configuration techniques can generate from this template new ABC variants that perform better than known ABC algorithms, even when their numerical parameters are fine-tuned using the same automatic configuration process.

中文翻译：

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ABC-X：一种通用的，可自动配置的人工蜂群框架

人工蜂群（ABC）算法是一种流行的元启发式算法，最初是为解决连续功能优化任务而构思的。在过去的十年中，已经提出了许多ABC变体，从而使它成为一种经过研究的群智能算法。通常，在有关ABC算法的算法变体的论文中，修改了其算法成分中的一个或最多两个。可能的变化包括搜索方程式的变化，要探索的候选解的选择或采用其他算法技术的特征。在本文中，我们建议遵循不同的方向，并建立一个通用的ABC算法，我们称之为ABC-X。ABC-X将可从已知ABC算法获得的算法组件收集到一个通用算法框架中，该框架不仅可以实例化已知ABC变体，而且更重要的是，还可以实例化文献中从未探索过的许多ABC算法变体。自动算法配置技术可以从该模板生成新的ABC变体，即使使用相同的自动配置过程对其数字参数进行微调，其性能也比已知的ABC算法更好。