Optical microscope algorithm: A new metaheuristic inspired by microscope magnification for solving engineering optimization problems

计算机科学 元启发式 放大倍数 显微镜 算法 模拟退火 人工智能 光学 物理
作者
Min‐Yuan Cheng,Moh Nur Sholeh
出处
期刊:Knowledge Based Systems [Elsevier BV]
卷期号:279: 110939-110939 被引量:46
标识
DOI:10.1016/j.knosys.2023.110939
摘要

A novel optimization algorithm called the optical microscope algorithm (OMA) is developed and applied in this study. Drawing inspiration from the magnification capabilities of an optical microscope on the target object, OMA uses the naked eye for initial observation and simulates the magnification process through an objective lens and an eyepiece. The performance of OMA, which is user friendly and does not require predefined operating parameters, is validated through two experiments: (1) OMA is compared to nine well-known metaheuristic algorithms using constraint handling with 50 benchmark functions involving multiple dimensions. The results indicate that OMA consistently outperforms all other algorithms and requires a short computational time. (2) OMA is applied to solve engineering problems, including structural optimization and multiple resources leveling in the multiple projects scheduling (MRLMP). In those cases, OMA not only demonstrates superiority but also requires the fewest evaluations of objective functions. The novel OMA, which is robust, easy to implement, and uses fewer control parameters, can be deployed to solve for various numerical optimization problems. The source code of OMA is publicly accessible at https://www.mathworks.com/matlabcentral/fileexchange/134541-optical-microscope-algorithm-oma.

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