A new adaptive evolutionary algorithm for design optimization - Eric Demetrius de Castro Barroca (2019)
In this work a new adaptive evolutionary algorithm derived from a stochastic algorithm for design optimization called Generalized Extremal Optimization (GEO) is introduced. It eliminates the single free parameter of GEO by controlling its value during the search by an adaptive approach which improved GEO performance significantly, even when considering the best GEO configurations. Nonetheless, it maintains the algorithm principal characteristics of dealing with continuous, discrete and integer design variables on convex or disjoint spaces while respecting design constrains. This new algorithm, called Adaptive Generalized Extremal Optimization (A-GEO), is implemented in two variations and applied to a multidisciplinary optimization problem of spacecraft engineering, showing the potential of the new methods in solving real engineering problems.