Global Performance Test of Metaheuristics Optimization and Engineering Applications
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Abstract
In this research study, 10 of the latest metaheuristics' performance characteristics are compared in the context of 19 unconstrained benchmark functions, where the large dimension of the test challenge is 100. Optimization problems may often encompass a large number of design variables, exerting complex effects upon the specific objective function. The performance is evaluated as the algorithm seeks a global optimum and avoids becoming trapped in a local optimum through the use of best values, mean and standard deviation (Stdev.). This study also uses Friedman Aligned Ranks and applies the Quade Ranks test to examine the differences in performance as the algorithms seek their solutions. Analysis of exploitation is conducted using Friedman Aligned Rank tests, while exploration is addressed using the Quade Ranks test. The study revealed that the different algorithms use different approaches to look for their solutions, with a significance level of 0.05. Finally, the comparison of the ten algorithms' performance is presented in this paper in the context of solving constrained mechanical and chemical engineering problems.
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