Blum Christian
Artificial Intelligence Research Institute (IIIA-CSIC), Campus of the UAB, Bellaterra, 08193, Barcelona, Spain.
Phys Life Rev. 2024 Dec;51:87-95. doi: 10.1016/j.plrev.2024.09.014. Epub 2024 Sep 26.
This paper is a follow-up of one of the most-cited articles published in the first 20 years of the existence of Physics of Life Reviews. The specific topic is "ant colony optimization", which is a metaheuristic for solving challenging optimization problems. Due to its inspiration from natural ant colonies' shortest path-finding behavior, this optimization technique forms part of a larger field known as swarm intelligence. After a short introduction to ant colony optimization, we first provide a chronology focusing on algorithmic developments rather than applications. The main part of the paper deals with a bibliometric study of the ant colony optimization literature. Interesting trends concerning, for example, the geographic origin of publications and the change in research focus over time, can be learned from the presented graphs and numbers.
本文是对《生命物理学评论》创刊20年来被引用次数最多的文章之一的后续研究。具体主题是“蚁群优化”，它是一种用于解决具有挑战性的优化问题的元启发式算法。由于它从自然蚁群的最短路径寻找行为中获得灵感，这种优化技术是被称为群体智能的更大领域的一部分。在对蚁群优化进行简短介绍之后，我们首先提供一个按时间顺序排列的内容，重点是算法的发展而非应用。本文的主要部分是对蚁群优化文献的文献计量学研究。从所呈现的图表和数据中，可以了解到一些有趣的趋势，例如出版物的地理来源以及研究重点随时间的变化。
