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

算法 优化算法 水准点(测量) 元启发式 计算机科学 数学 数学优化 地质学 大地测量学
作者
Eva Trojovská,Mohammad Dehghani,Pavel Trojovský
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:10: 49445-49473 被引量:235
标识
DOI:10.1109/access.2022.3172789
摘要

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.
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