Artificial Protozoa Optimizer (APO): A novel bio-inspired metaheuristic algorithm for engineering optimization

TL;DR

This paper introduces the Artificial Protozoa Optimizer (APO), a new bio-inspired metaheuristic algorithm modeled after protozoa behaviors, demonstrating competitive performance on benchmark and real-world engineering problems.

Contribution

The paper presents the first metaheuristic algorithm inspired by protozoa, with a detailed mathematical model and extensive experimental validation against state-of-the-art methods.

Findings

APO outperforms or matches 32 existing algorithms on benchmark functions.

APO effectively solves engineering design problems with constraints.

APO successfully applied to discrete space image segmentation.

Abstract

This study proposes a novel artificial protozoa optimizer (APO) that is inspired by protozoa in nature. The APO mimics the survival mechanisms of protozoa by simulating their foraging, dormancy, and reproductive behaviors. The APO was mathematically modeled and implemented to perform the optimization processes of metaheuristic algorithms. The performance of the APO was verified via experimental simulations and compared with 32 state-of-the-art algorithms. Wilcoxon signed-rank test was performed for pairwise comparisons of the proposed APO with the state-of-the-art algorithms, and Friedman test was used for multiple comparisons. First, the APO was tested using 12 functions of the 2022 IEEE Congress on Evolutionary Computation benchmark. Considering practicality, the proposed APO was used to solve five popular engineering design problems in a continuous space with constraints. Moreover, the APO was applied to solve a multilevel image segmentation task in a discrete space with constraints. The experiments confirmed that the APO could provide highly competitive results for optimization problems. The source codes of Artificial Protozoa Optimizer are publicly available at https://seyedalimirjalili.com/projects and https://ww2.mathworks.cn/matlabcentral/fileexchange/162656-artificial-protozoa-optimizer.