Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm

In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration is the behavior of zebras in nature. ZOA simulates the foraging behavior of zebras and their defense strategy against predators' attacks. The ZOA steps a...

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Published inIEEE access Vol. 10; pp. 49445 - 49473
Main Authors Trojovska, Eva, Dehghani, Mohammad, Trojovsky, Pavel
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration is the behavior of zebras in nature. ZOA simulates the foraging behavior of zebras and their defense strategy against predators' attacks. The ZOA steps are described and then mathematically modeled. ZOA performance in optimization is evaluated on sixty-eight benchmark functions, including unimodal, high-dimensional multimodal, fixed-dimensional multimodal, CEC2015, and CEC2017. The results obtained from ZOA are compared with the performance of nine well-known algorithms. The simulation results show that ZOA can solve optimization problems by creating a suitable balance between exploration and exploitation and has a superior performance compared to nine competitor algorithms. ZOA's ability to solve real-world problems has been tested on four engineering design problems, namely, tension/compression spring, welded beam, speed reducer, and pressure vessel. The optimization results show that ZOA is an effective optimizer in determining the values of the design variables of these problems compared to the nine competitor algorithms.
AbstractList In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration is the behavior of zebras in nature. ZOA simulates the foraging behavior of zebras and their defense strategy against predators' attacks. The ZOA steps are described and then mathematically modeled. ZOA performance in optimization is evaluated on sixty-eight benchmark functions, including unimodal, high-dimensional multimodal, fixed-dimensional multimodal, CEC2015, and CEC2017. The results obtained from ZOA are compared with the performance of nine well-known algorithms. The simulation results show that ZOA can solve optimization problems by creating a suitable balance between exploration and exploitation and has a superior performance compared to nine competitor algorithms. ZOA's ability to solve real-world problems has been tested on four engineering design problems, namely, tension/compression spring, welded beam, speed reducer, and pressure vessel. The optimization results show that ZOA is an effective optimizer in determining the values of the design variables of these problems compared to the nine competitor algorithms.
Author Trojovsky, Pavel
Trojovska, Eva
Dehghani, Mohammad
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Snippet In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration is the behavior...
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StartPage 49445
SubjectTerms Algorithms
Bio-inspired
Biological system modeling
Compression springs
Design engineering
engineering design
exploitation
exploration
Heuristic methods
Linear programming
Mathematical models
Metaheuristics
Optimization
Optimization algorithms
Performance evaluation
Pressure vessels
Search problems
Sociology
Statistics
zebra
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  providerName: IEEE
Title Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm
URI https://ieeexplore.ieee.org/document/9768820
https://www.proquest.com/docview/2663643664
https://doaj.org/article/7298d05fcc2d424cb4490e8dccc6ac78
Volume 10
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