Optimization of p-xylene oxidation reaction process based on self-adaptive multi-objective differential evolution

• A multi-objective optimization problem is designed for PX oxidation reaction process.
• Self-adaptive multi-objective differential evolution (SADE) is used to solve this MOP.
• SADE's trial vector generation strategies and control parameters are self-adjusted.
• Pseudo feasible concept is proposed to effectively handle constraints.

Purified terephthalic acid (PTA) is used for producing a variety of polyesters. In the production of PTA, p-xylene (PX) is first transformed into terephthalic acid (TA) by oxidation process and then TA is refined. As a key step, the oxidation of PX to TA is a significant chemical process of PTA production. To improve qualified product yield with low energy consumption, in this paper, multi-objective optimization of various conflicting objectives (namely minimization of combustion loss, maximization of TA yield) is conducted using self-adaptive multi-objective differential evolution algorithm (SADE). The main characteristic of it is that DE's trial vector generation strategies and the corresponding control parameters are gradually self-adjusted adaptively based on the knowledge learnt from the previous searches in generating improved solutions. Furthermore, to handle constraints in multi-objective problems, the pseudo feasible concept is proposed to effectively utilize the critical information carried by some infeasible solutions. Optimization results of PX oxidation reaction process indicate that application of SADE can greatly improve the yield of TA with low combustion loss without degenerating TA quality. Furthermore, SADE can provide a set of Pareto optimal solutions and then suitable multi-criterion decision-making techniques can be employed to select one or a small set of the optimal solution(s) of design parameter(s) based on preference.