Abstract
This paper introduces a robust and global algorithm, the multi-objective version of the Set Trimming method (MOST). The application of MOST is demonstrated through optimization of a plate and fin heat exchanger. The results are compared with NSGA-II (Fast and elitism non-dominated sorting Genetic Algorithm) and an exhaustive search. The optimization focuses on effectiveness and annual cost, with seven selected design parameters and for six different cases. Results indicate that the Pareto optimal fronts obtained with NSGA-II are entirely dominated by those achieved using MOST in the all studied cases. Furthermore, MOST improves annual cost for the best economic point solution by up to 13.44% as compared to NSGA-II. Simultaneously, effectiveness is enhanced up to 0.04% when using MOST compared to NSGA-II. The computational time is also improved with the presented optimization algorithm compared to NSGA-II in the range of 78.6–88.8%.
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