Optimisation Methodologies and Algorithms for Research on Catalysis Employing High-Throughput Methods: Comparison Using the Selox Benchmark

摘要

The Selox is a catalytic benchmark for the selective CO oxidation reaction in the presence of H2, in the form of mathematical equations obtained via modelling of experimental results. The optimisation efficiencies of several Global Optimisation algorithms were studied using the Selox benchmark. Genetic Algorithms, Evolutionary Strategies, Simulated Annealing, Taboo Search and Genetic Algorithms hybridised with Knowledge Discovery procedures were the methods compared. A Design of Experiments search strategy was also exemplified using this benchmark. The main differences regarding the applicability of DoE and Global optimisation techniques are highlighted. Evolutionary strategies, Genetic algorithms, using the sharing procedure, and the Hybrid Genetic algorithms proved to be the most successful in the benchmark optimisation.