A modified imperialist competitive algorithm for constrained optimization of plate-fin heat exchangers

Abstract

In this study, to handle the design optimization of plate-fin heat exchangers, a constrained version of a newly introduced evolutionary algorithm, the imperialist competitive algorithm, is proposed. Imperialist competitive algorithm was initially established for unconstrained optimization problems and different strategies such as penalty functions were employed to handle the constraints in the previous studies. In the proposed constrained imperialist competitive algorithm, a feasibility-based ranking is employed in the imperialist competitive algorithm method. Seven design parameters and various constraints are considered for the design optimization in which minimum weight and minimum total annual cost were considered as the autonomous objective functions. The results are compared with those obtained by a genetic algorithm approach combined with a static penalty function scheme. Also, a comparison between the proposed algorithm and the original imperialist competitive algorithm is performed. The simulation results show that both the proposed algorithm and imperialist competitive algorithm are of higher accuracy than the genetic algorithm, which is commonly used. Also, the numerical experiment indicates that the modification in the imperialist competitive algorithm leads to better performance of the algorithm.