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

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. (c) 2023 Elsevier B.V. All rights reserved.