Design of heat exchangers using Falcon Optimization Algorithm

This paper proposes a novel metaheuristic optimizer based on the hunt behavior of falcons called Falcon Optimization Algorithm (FOA). FOA is a robust and powerful stochastic population-based algorithm that needs the adjustment of few parameters for its three-stage movement decision. Simulation results based on well-known twelve benchmark single-objective functions demonstrate the efficiency, effectiveness and robustness of the proposed method in comparison to other algorithms. Furthermore, the results of its single-objective application in heat exchangers shell-and-tube and plate-fin types allowed better results than previous works for the objective functions total cost for shell-and-tube heat exchanger (28% and 57.8% of reduction for cases 1 and 2, respectively) and number of entropy generation units (15.42% of reduction for case 1) and effectiveness (10% of increasing for case 2) for plate-fin heat exchanger type, alongside with a thermal-hydraulic discussion. Moreover, the FOA reached some solutions better than those previously reported in the literature.