Artificial gorilla troops algorithm for the optimization of a fine plate heat exchanger

Adaptability of the metaheuristic (MH) algorithms in multidisciplinary platforms confirms its significance and effectiveness for the solution of the constraints problems. In this article, one of the imperative thermal system components-plate fin heat exchangers is economically optimized using the novel artificial gorilla troops optimization algorithms (AGTOAs). The cost optimization challenge of the PFHE includes the initial and running cost that needs to be minimized by optimizing several design variables subjecting to critical boundary conditions. To confirm the performance of the AGTOA, the statistical results obtained were compared with nine benchmark MHs algorithms. It was found that AGTO is a robust optimization algorithm because it was able to fetch the best results for the function with 100% of the success rate compared to the rest of the algorithms. Moreover, considering the superior results obtained from the AGTO, it can be applied to numerous applications of the engineering design optimization.

Automated summary

This article introduces a novel metaheuristic algorithm (AGTOA) for the optimization of thermal system components. By comparing with nine benchmark algorithms, the results show that AGTOA is a powerful optimization algorithm that can be applied to various engineering design optimization applications.