Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using genetic algorithm (GA) with the jumping genes operator

@article{Kasat2003MultiobjectiveOO,
  title={Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using genetic algorithm (GA) with the jumping genes operator},
  author={Rahul B. Kasat and Santosh Kumar Gupta},
  journal={Computers & Chemical Engineering},
  year={2003},
  volume={27},
  pages={1785-1800}
}
The multi-objective optimization of industrial operations using genetic algorithm and its variants, often requires inordinately large amounts of computational (CPU) time. Any adaptation to speed up the solution procedure is, thus, desirable. An adaptation is developed in this study that is inspired from natural genetics. It is based on the concept of jumping genes (JG; transposons). The binary-coded elitist non-dominated sorting genetic algorithm (NSGA-II) is adapted, and the new code, NSGA-II… CONTINUE READING
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