In the recent years, extensive discussion takes place in literature, on the effectiveness of meta-heuristics, and especially Nature Inspired Algorithms. Usually, authors state that such an approach should embody a well-balanced exploration and exploitation strategy. Sonar Inspired Optimization (SIO) is a recently presented algorithm, which counts already a number of successful real-world applications. Its novel mechanisms provide this equilibrium between exploration and exploitation, as it has been stated in previous studies. In this work, authors prove that this equilibrium exists and also, it is one of the main reasons behind the high quality performance of SIO.

近年来，文献中对元启发式算法的有效性进行了广泛的讨论，尤其是自然启发算法。通常，作者声明这种方法应该体现平衡的探索和开发策略。声纳启发优化 (SIO) 是最近提出的算法，它已经计算了许多成功的实际应用程序。正如之前的研究中所述，其新颖的机制在探索和开发之间提供了这种平衡。在这项工作中，作者证明了这种平衡是存在的，这也是 SIO 高质量性能背后的主要原因之一。