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Stochastic process and tutorial of the African buffalo optimization
Julius Beneoluchi Odili1, A Noraziah2,3, Basem Alkazemi4
1Faculty of Science and Science Education, Anchor University Lagos, Lagos, Nigeria. odili_julest@yahoo.com.
Scientific Reports
|October 15, 2022
Summary
The African buffalo optimization algorithm (ABO) is a novel metaheuristic inspired by buffalo herd behavior. This paper details its mechanics, aiding researchers in applying this new population-based optimization technique.
Area of Science:
- Computational Intelligence
- Metaheuristic Optimization
- Nature-Inspired Algorithms
Background:
- Elaborate descriptions of optimization algorithm mechanics are scarce in scientific literature.
- Reproducibility and user-friendliness of novel algorithms are crucial for research advancement.
- Population-based optimization algorithms are widely used in solving complex problems.
Purpose of the Study:
- To provide a comprehensive data description and manual of the African buffalo optimization algorithm (ABO).
- To enhance the user-friendliness and reproducibility of the ABO algorithm.
- To introduce a novel nature-inspired optimization algorithm to the research community.
Main Methods:
- The African buffalo optimization algorithm (ABO) is developed based on the migratory behavior and communication patterns of African buffalo herds.
- The algorithm's fundamental flow, stochastic processes, and data generation mechanisms are described in detail.
- The ABO algorithm is implemented and tested on benchmark functions, including Rosenbrock and Shekel Foxhole.
Main Results:
- The paper provides a clear and accessible description of the ABO algorithm's workings.
- Experimental results demonstrate the effectiveness of the ABO algorithm.
- Benchmarking against established algorithms like Cuckoo Search and Flower Pollination Algorithm shows competitive performance.
Conclusions:
- The African buffalo optimization algorithm (ABO) is presented as a valuable addition to the field of population-based optimization.
- The detailed description facilitates understanding, application, and reproducibility of the ABO algorithm.
- The ABO algorithm shows promise for solving complex optimization problems effectively.
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