Optimum air cooling cost by T.L.B.O.
DOI:
https://doi.org/10.37255/jme.v20i3pp095-099Keywords:
TLBO algorithm , optimum cost, air cooling systemAbstract
This paper presents the performance of the Teaching-Learning-Based Optimization (T.L.B.O.) algorithm for the optimum design of an air cooling system. The optimal cost of an air cooling system is investigated using the TLBO algorithm and compared with other optimization algorithms, including the Lagrange Multipliers (LM) method, Differential Evolution (DE) algorithm, and Particle Swarm Optimization (PSO) algorithm. TLBO is a recently proposed population-based algorithm that simulates the teaching-learning process in a classroom. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. Computational results demonstrate that the TLBO algorithm is successfully applied to the air cooling system, exhibiting better performance compared to other optimization algorithms considered for this problem.
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