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Can genetic algorithm be used to find two independent optimum operating conditions for predefined input and output ?
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I've built a moving bed biomass torrefaction reactor which is controlled by the speed of the conveying mechanism and the air mass flow rate fed for combustion with the released volatiles to give a certain temperature. I have included all the related equations of reactor behavior into a straightforward Matlab code where I define the input characteristics of biomass and the operating conditions and then the code gives the output characteristics for such conditions. Now I want to get the optimum operating conditions (time in terms of conveyor speed and temperature in terms of air mass flow rate) to reach a predefined output (biomass characteristics). I'm not familiar with optimization techniques but after some research I got to know that genetic algorithm is the most used algorithm for optimization. So, I'm asking if it can be of help for my concern and if so, is there a guide to do such optimization?
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Star Strider
el 29 de Oct. de 2019
Optimisation functions, including the genetic algorithm (ga function) optimise a set of parameters to produce the desired result. It is certainly possible to create a fitness function that will optimise your model, however it would be necessary to see the model in order to determine the best approach.
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Alan Weiss
el 29 de Oct. de 2019
It sounds to me as if you are trying to optimize an ODE system, possibly fitting the parameters to an existing function. If I understand that correctly, then I suggest that you look at these examples:
Alan Weiss
MATLAB mathematical toolbox documentation
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