In this paper, first, a first-principle model is built by including
extra formation of acetaldehyde, which has been largely neglected in the
literature. Second, there exist four objectives to optimize in the
process of esterification, including rate of esterification, average
molecular weight, degree of polymerization and diethylene glycol content
percentage. However, most researchers have considered only one or two of
the four performance indicators which may not completely reflect the
actual state of PET polymerization process. In this work, an improved
RVEA algorithm, called PARVEA, is proposed to deal with a four-objective
optimization problem combining with a new first-principle model in
esterification process. Simulation results prove the effectiveness of
the proposed PARVEA algorithm. Finally, companies can choose more
suitable solutions and process parameters according to user preferences,
which can meet the requirements for differentiated production of
high-quality polyester fiber polymer