Multi objective design optimization of plate fin heat sinks using improved differential search algorithm

Abstract

This study provides the multi-objective optimization of plate fin heat sinks equipped with flow – through and impingement-flow air-cooling system by using Improved Differential Search algorithm. Differential Search algorithm mimics the subsistence characteristics of the living beings through the migration process. Convergence speed of the algorithm is enhanced with the local search based perturbation schemes and this improvement yields favorable solution outputs according to the results obtained from the widely quoted optimization test problems. Improved algorithm is employed on multi-objective design optimization of plate fins heat sink considering the objective functions of entropy generation rate and total material cost. Total of seven decision variables such as oncoming stream velocity, number of fins on the plate, gap between consecutive fins, base thickness of the plate, width, length and height of the plate fin heat sink are selected to be optimized. Pareto frontiers are constructed for both flow-through and impingement flow air-cooling system design and best solutions are obtained by means of widely reputed decision-making theories of LINMAP, TOPSIS, and Shannon’s entropy theory. Results retrieved from the case studies show that reliable outcomes could be achieved in terms of solution accuracy through Improved Differential Search optimizer.