Abstract
Constrained evolutionary optimization algorithms for Integrate and Fire (IAF) classical retina model are programmed. The techniques applied are Pareto-Multiobjective (PMO) methods. Genetic Algorithm (GA) software is developed based on literature neuro-bioelectronics experimental dataset. Results take in handle subroutines functions and matrix-algebra method for setting constraints. Results show PMO 2D imaging charts and numerical values for IAF model, with optimal values for IS Input Current (IC) parameter. Bioelectronics applications for human vision improvements and extrapolation to life-origin pre-hypotheses are briefed.
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