Multi-objective thermal design optimization of plate frame heat exchangers through Global Best Algorithm
This study deals with thermal design of plate frame heat exchangers based on Global Best Algorithm. By utilizing some basic perturbation schemes adopted from Differential Search and Differential Evolution, Global Best Algorithm aims to obtain optimum solution of any optimization problem with intensifying on exploitiation of the promising solutions rather than exploring of the unvisited paths of the search domain. Firstly, optimization performance of the proposed algorithm has been benchmarked against variety of well-known optimization algorithms by means of 16 different highly challenging optimization test functions. Then, the proposed method is put into practice to acquire the optimal values of the design variables those optimize the considered problem objectives including overall heat transfer coefficient, total cost and weight of the plate frame heat exchangers seperately as well as simultaneously. Considerable improvement in objective function values is observed as compared to preliminary design in single objective manner. Pareto frontier is constructed for dual and triple objective and best optimal solution among the curve is selected by means of the widely-known decision making methods of LINMAP, TOPSIS, and Shannon’s entropy theory. Optimal results obtained from each decision making theory are compared with respect to their corresponding deviation indexes and the best one is preferred. A sensitivity analysis is then performed to study the variational influences of some design parameters on the considered objective functions. It is observed that selected design variables has a signficant effect on problem objectives.
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