An improved particle swarm algorithm for optimal design of plate-fin heat exchangers

In this paper, an improved particle swarm optimization (PSO) was used to optimize the structure dimensions of the plate-fin heat exchangers (PFHEs). The major objectives are to minimize the total weight and total annual cost of the PFHEs for given constrained conditions. The total weight target ensures an exchanger of the smallest size with minimum capital cost, whereas the annual cost target yields the optimum pressure drops accounting for the trade-off between power consumption and heat exchanger weight. The total length and width of the PFHE core, number of hot side layers, fin height, and pitch on each side of the PFHE are considered as optimization variables. The logarithmic mean temperature difference method is used for the design of the PFHE. Also compared with the results obtained by PSO and the traditional genetic algorithm, the PSO algorithm presents a shorter computational time and better results under the same design parameters and the same optimization variables.