Optimization of compact heat exchangers by a genetic algorithm

In this study a plate–fin type Compact Heat Exchanger (CHE) is considered for optimization. The optimization method uses a Genetic Algorithm (GA) to search, combine and optimize structure sizes of the CHE. The minimum total volume or/and total annual cost of the CHE are taken as objective functions in the GA, respectively. The geometries of the fins are fixed while three shape parameters are varied for the optimization objectives with or without pressure drop constraints, respectively. Performance of the CHE is evaluated according to the conditions of the structure sizes that the GA generated, and the corresponding volume and cost are calculated. It is shown that with pressure drop constraints the optimized CHE provides about 30% lower volume or about 15% lower annual cost, while without pressure drop constraints the optimized CHE provides about 49% lower volume or about 16% lower annual cost than those presented in the literature.