Optimization of Engineering Design Problems Using Atomic Orbital Search Algorithm
Optimization of Engineering Design Problems Using Atomic Orbital Search Algorithm
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DOI：
10.1109/access.2021.3096726
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发表时间：
2021-01-01
期刊：
影响因子：
3.9
通讯作者：
Giaralis, Agathoklis
中科院分区：
文献类型：
--
作者：
Azizi, Mahdi;Talatahari, Siamak;Giaralis, Agathoklis
本文采用最近提出的一种新的启发式优化算法--原子轨道搜索法（AOS）来解决工程问题的优化设计问题。该算法的数学发展是基于量子力学的原理，专注于原子核周围电子的行为。对于数值研究，考虑了不同工程领域中20个众所周知的约束设计问题;其中一些已经被2020年进化计算竞赛（CEC 2020）用于现实世界的优化目的。报告了AOS算法的统计结果，包括多次优化运行的最佳、平均、最差和标准差。这些结果进行了比较，从以前的元启发式算法在文献中发现的类似数据，以建立AOS的效率和实用性。它的结论是，AOS具有可接受的行为在处理所有考虑的约束优化问题，而AOS和其他方法的最佳最优值之间的最大差异约40%，注意到机器人夹持器基准问题。
In this paper, optimum design of engineering problems is considered by means of the Atomic Orbital Search (AOS), a recently proposed metaheuristic optimization algorithm. The mathematical development of the algorithm is based on principles of quantum mechanics focusing on the act of electrons around the nucleus of an atom. For numerical investigation, 20 of well-known constrained design problems in different engineering fields are considered; some of which have been benchmarked by the 2020 Competitions on Evolutionary Computation (CEC 2020) for real-world optimization purposes. Statistical results including the best, mean, worst and standard deviation of multiple optimization runs are reported for the AOS algorithm. These results are compared to similar data from previous metaheuristic algorithms found in the literature to establish the efficiency and usefulness of the AOS. It is concluded that the AOS has acceptable behavior in dealing with all the considered constrained optimization problems while the maximum difference of about 40% between the best optimum values of the AOS and other approaches is noted for the robot gripper benchmark problem.