Anti-Predatory NIA for Unconstrained Mathematical Optimization Problems

Rohit Kumar Sachan and Dharmender Singh Kushwaha
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Rohit Kumar Sachan: Motilal Nehru National Institute of Technology Allahabad, Allahabad, India
Dharmender Singh Kushwaha: Motilal Nehru National Institute of Technology Allahabad, Allahabad, India

International Journal of Swarm Intelligence Research (IJSIR), 2020, vol. 11, issue 1, 1-23

Abstract: Nature-Inspired Algorithms (NIAs) are one of the most efficient methods to solve the optimization problems. A recently proposed NIA is the anti-predatory NIA, which is based on the anti-predatory behavior of frogs. This algorithm uses five different types of self-defense mechanisms in order to improve its anti-predatory strength. This paper demonstrates the computation steps of anti-predatory for solving the Rastrigin function and attempts to solve 20 unconstrained minimization problems using anti-predatory NIA. The performance of anti-predatory NIA is compared with the six competing meta-heuristic algorithms. A comparative study reveals that the anti-predatory NIA is a more promising than the other algorithms. To quantify the performance comparison between the algorithms, Friedman rank test and Holm-Sidak test are used as statistical analysis methods. Anti-predatory NIA ranks first in both cases of “Mean Result” and “Standard Deviation.” Result measures the robustness and correctness of the anti-predatory NIA. This signifies the worth of anti-predatory NIA in the domain of mathematical optimization.

Date: 2020
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