Application of the generalized extremal optimization algorithm to an inverse radiative transfer problem

Abstract

The recently developed generalized extremal optimization (GEO) algorithm is applied for the solution of an inverse problem of radiative properties estimation. A comparison with two other stochastic methods, simulated annealing and genetic algorithms, is also performed, demonstrating that GEO is competitive. From the test case results we could also infer that a hybridization of GEO with gradient-based methods is very promising.