Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and ideas behind the proposed algorithm are the cooper...

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Bibliographic Details
Published in:Mathematics (Basel) 2021-12, Vol.9 (23), p.3011
Main Author: Yadav, Drishti
Format: Article
Language:English
Subjects:
Algorithms
bio-inspired algorithms
Blood
Blood coagulation
Blood Coagulation Algorithm
Blood vessels
Comparative studies
Design engineering
Design optimization
Diversification
Food science
Global optimization
Heuristic
Heuristic methods
Mathematical models
meta-heuristics
nature-inspired meta-heuristics
optimization
Optimization algorithms
Statistical tests
swarm intelligence
Thrombocytes
Topography
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Summary:This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and ideas behind the proposed algorithm are the cooperative behavior of thrombocytes and their intelligent strategy of clot formation. These behaviors are modeled and utilized to underscore intensification and diversification in a given search space. A comparison with various state-of-the-art meta-heuristic algorithms over a test suite of 23 renowned benchmark functions reflects the efficiency of BCA. An extensive investigation is conducted to analyze the performance, convergence behavior and computational complexity of BCA. The comparative study and statistical test analysis demonstrate that BCA offers very competitive and statistically significant results compared to other eminent meta-heuristic algorithms. Experimental results also show the consistent performance of BCA in high dimensional search spaces. Furthermore, we demonstrate the applicability of BCA on real-world applications by solving several real-life engineering problems.
ISSN:2227-7390
2227-7390
DOI:10.3390/math9233011