.png){kind=icon}
.png){kind=icon}
Return
Artificial protozoa optimizer: A bio-inspired metaheuristic for complex engineering optimization
.png){kind=icon}
OA
AI
DOI：10.1016/j.rineng.2025.106883.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• New optimizer inspired by the movement and survival of protozoa. • Combines targeted search, local refinement, and learning from past steps. • Finds best results in most standard test problems for optimization. • Performs among the top three in challenging global search tasks. • Solves real-world design problems with high accuracy and reliability.
Keywords:
Artificial protozoa optimizer
Bio-inspired metaheuristics
High-dimensional optimization
Engineering design problems
CEC benchmark functions
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.9
Papers:
1.1W
Citations:
1.7W
Organization
No organization information available