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Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems

Authors :
Osama Al-Baik
Saleh Alomari
Omar Alssayed
Saikat Gochhait
Irina Leonova
Uma Dutta
Om Parkash Malik
Zeinab Montazeri
Mohammad Dehghani
Source :
Biomimetics, Vol 9, Iss 2, p 65 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

A new bio-inspired metaheuristic algorithm named the Pufferfish Optimization Algorithm (POA), that imitates the natural behavior of pufferfish in nature, is introduced in this paper. The fundamental inspiration of POA is adapted from the defense mechanism of pufferfish against predators. In this defense mechanism, by filling its elastic stomach with water, the pufferfish becomes a spherical ball with pointed spines, and as a result, the hungry predator escapes from this threat. The POA theory is stated and then mathematically modeled in two phases: (i) exploration based on the simulation of a predator’s attack on a pufferfish and (ii) exploitation based on the simulation of a predator’s escape from spiny spherical pufferfish. The performance of POA is evaluated in handling the CEC 2017 test suite for problem dimensions equal to 10, 30, 50, and 100. The optimization results show that POA has achieved an effective solution with the appropriate ability in exploration, exploitation, and the balance between them during the search process. The quality of POA in the optimization process is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that POA provides superior performance by achieving better results in most of the benchmark functions in order to solve the CEC 2017 test suite compared to competitor algorithms. Also, the effectiveness of POA to handle optimization tasks in real-world applications is evaluated on twenty-two constrained optimization problems from the CEC 2011 test suite and four engineering design problems. Simulation results show that POA provides effective performance in handling real-world applications by achieving better solutions compared to competitor algorithms.

Details

Language :
English
ISSN :
23137673
Volume :
9
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Biomimetics
Publication Type :
Academic Journal
Accession number :
edsdoj.fe46c86e46e54dac8fc4ff00bcbe7687
Document Type :
article
Full Text :
https://doi.org/10.3390/biomimetics9020065