Multi-objective optimization of a direct methanol fuel cell system using a genetic-based algorithm


Correspondence: Suha Orçun Mert, Department of Chemical Engineering, Ege University, İzmir, Turkey.



The multi-objective optimization of a direct methanol fuel cell system was conducted with the objective functions of maximizing both the power output and energy and exergy efficiencies depending on the comprehensive exergy analysis of this study. This advanced model is mounted into the developed computer program multi-objective optimizer which is based on an improved genetic algorithm. The problem is solved parametrically depending on the on the multi-objective optimization objective function ratios which allows a chance to investigate the trade-offs and the importance of the objectives. The investigated parameters are the varying available operating conditions, such as temperature, concentration, and current density. The best results found for each objective were 9.72 W for the power produced and 10.732 and 10.467 energy and exergy efficiency, respectively. However, the best optimum for the overall investigation, taking the fitness function into consideration, was 9.59 W for the power and 10.248 and 9.995 energy and exergy efficiencies. Copyright © 2012 John Wiley & Sons, Ltd.