Surrogate-model-based, particle swarm optimization, and genetic algorithm techniques applied to the multiobjective operational problem of the fluid catalytic cracking process

Surrogate-model-based, particle swarm optimization, and genetic algorithm techniques applied to the multiobjective operational problem of the fluid catalytic cracking process

Jose F. Cuadros Bohorquez, Laura Plazas Tovar, Maria Regina Wolf Maciel, Delba C. Melo, Rubens Maciel Filho

ARTIGO

Inglês

This article provides a concise multiobjective optimization methodology for an industrial fluid catalytic cracking unit (FCCU) considering stochastic optimization techniques, genetic algorithms (GA) and particle swarm optimization (PSO), based on surrogates or meta-models in order to approximate the...

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

Fechado

Surrogate-model-based, particle swarm optimization, and genetic algorithm techniques applied to the multiobjective operational problem of the fluid catalytic cracking process

Jose F. Cuadros Bohorquez, Laura Plazas Tovar, Maria Regina Wolf Maciel, Delba C. Melo, Rubens Maciel Filho


										

Surrogate-model-based, particle swarm optimization, and genetic algorithm techniques applied to the multiobjective operational problem of the fluid catalytic cracking process

Jose F. Cuadros Bohorquez, Laura Plazas Tovar, Maria Regina Wolf Maciel, Delba C. Melo, Rubens Maciel Filho

    Fontes

    Chemical engineering communications

    Vol. 207, no. 5 (May, 2020), p. 612-631