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.

Keywords:

• Inverse problems
• Radiative transfer
• Optimization
• Generalized extremal optimization

Acknowledgments

The authors acknowledge the financial support provided by CNPq – Conselho Nacional de Desenvolvimento Científico e Tecnológico, CAPES – Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, and FAPERJ - Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro.