Optimization of plate-fin heat exchangers by an improved harmony search algorithm

This study explores the use of a proposed variant of harmony search algorithm for design optimization of plate-fin heat exchangers. The algorithm deals with a large number of continuous and discrete variables. To handle the constraints in the optimization problem, a self-adaptive penalty function scheme is used. The efficiency and accuracy of the proposed method are demonstrated through an illustrative example taken from previous studies. Numerical results indicate that the presented approach can generate optimum solutions with higher accuracy when compared to Genetic algorithms (GAs), Particle Swarm Optimization (PSO) and GA hybrids with PSO (GAHPSO).

► This is the first application of HS algorithm for plate-fin heat exchanger design. ► The original HS algorithm has been modified. ► A self-adaptive penalty function is used which eases the constraint handling. ► The results show the superiority of this method over GA, PSO and their hybrid.