Using Mealpy Open-Source Library for Optimization of Constrained Engineering Problems

Metaheuristic algorithms are widely used in the scientific community, with numerous algorithms inspired by various sources. Python programming language has become a valuable tool for implementing these algorithms in scientific research. This study uses the MEALPY Python open-source library to solve two constrained optimization problems from existing literature. The concept of the library is explained, and results for problems related to welded beam design and speed reducer designare obtained. Eight swarm-based algorithms from the library are selected for the comparative analysis. The results are compared and graphically presented in several figures. Discussion regarding the best fitness values, convergence, exploration and exploitation percentages, runtime, and trajectory of agents is made before concluding the study.