Fuzzy Multi-objective Particle Swarm Optimization Algorithm Using Industrial Purified Terephthalic Acid Solvent Dehydration Process

In this paper, a fuzzy multi-objective particle swarm optimization (MOPSO) based on Pareto dominance hybrid algorithm is investigated and applied in industrial purified terephthalic acid (called PTA) solvent dehydration process for the first time. Pareto dominance and fuzzy decision making are incorporated into particle swarm optimization. Our algorithm takes fuzzy Pareto set as repository of particles that is later used by other particles to guide their own flight. Additionally, an MOPSO and PTA hybrid model is applied in the operation optimization of industrial purified terephthalic acid solvent dehydration process. From both theoretical computation and practical application, the validity and reliability of proposed algorithm are verified by two test functions studied, and actual application example of the optimization of operation parameter of industrial purified terephthalic acid solvent dehydration process. In this study, a comprehensive model for an industrial Purified Terephthalic Acid solvent dehydration process is presented. The model parameters are tuned using industrial data. Complete details of the model are provided. Thereafter, a two-objective optimization of this PTA is performed; the concentrations of the acetic acid concentration in the tower bottom is maximized while the concentrations of the acetic acid concentration in the tower top is minimized. The Pareto solution of the fuzzy MOPSO is near the Pareto front.