A parallel between differential evolution and genetic algorithms with exemplification in a microfluidics optimization problem

This paper analyses two optimization procedures: one based on genetic algorithms and the other on differential evolution. We apply these algorithms on a particular problem from the field of microfluidics in order to demonstrate how they can be used in design optimization. The improvement of the results, and also the simplicity and flexibility of the algorithms encourages us to suggest the use of these techniques in other problems from other areas in MEMS design

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