Energy and cost optimization of a plate and fin heat exchanger using genetic algorithm

In the present paper, a plate and fin heat exchanger is considered and air, as an ideal gas, is defined in both sides of the heat exchanger as the working fluid. Several geometric variables within the logical constraints are considered as optimization parameters. Two different objective functions including the total rate of heat transfer and the total annual cost of the system are defined. Since mentioned objectives are conflicting, no single solution can well-satisfy both objective functions simultaneously. In other words, any attempt to increase the value of the total rate of heat transfer leads to the higher total cost of the system which is certainly undesirable. Therefore, multi-objective optimization using genetic algorithm is utilized in order to achieve a set of optimal solutions, each of which is a trade-off between objectives and can satisfy both objective functions in an appropriate level. The main advantage of this work is providing a set of optimal solutions each of which can be selected by the designer based on the project’s limits and the available investment. A sensitivity analysis is also presented in order to investigate the effect of some geometric parameters on each objective functions.