Further Commentary on the Sooty Tern Optimization Algorithm and Tunicate Swarm Algorithm

TL;DR

This paper critically analyzes the Sooty Tern Optimization Algorithm and Tunicate Swarm Algorithm, revealing that their design flaws cause bias issues, and emphasizes cautious application of these bio-inspired algorithms.

Contribution

It extends prior analysis by identifying probabilistic causes of bias in STOA and TSA, providing insights into their limitations and guiding better usage.

Findings

Operations like exponentiation and trigonometric functions cause bias.

Probability distributions shift toward zero due to certain operations.

Caution is advised when applying these algorithms.

Abstract

In the article (Kudela, 2022), experimental demonstrations indicated that two Bio-/Nature inspired optimization algorithms (BNIOAs), Sooty Tern Optimization Algorithm (STOA) and Tunicate Swarm Algorithm (TSA), exhibit a zero-bias, leading to the conclusion that the claims made in the original papers were overstated. In this work, we extend the analysis by investigating the source of this bias from a probabilistic perspective. Our findings suggest that operations involving exponentiation, trigonometric functions, and divisions between random numbers are the primary causes of design flaws. These operations result in probability density distributions with a noticeable shift toward zero. Therefore, the application of these two algorithms should be approached with due caution.