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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
il 29 Ott 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
il 29 Ott 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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