Dynamic Multi-objective Optimization of Chemical Process Based on Bare Bones Particle Swarm Optimization

Abstract

The purpose of this study is to improve the production efficiency and safety of chemical process. To this end, the dynamic multi-objective optimization of chemical process based on bare bones particle swarm optimization (BBPSO) was studied in this paper. Firstly, the algorithm of BBPSO was studied. On this basis, the algorithm was improved in terms of its search performance. Then, the constraint treatment method was designed and used for simulation experiments. Experimental results show that to produce the 6.125g of foreign protein, it only needs to add the 439ML inducer. Therefore, the proposed algorithm exhibits better convergence and distribution, achieving the optimization effect.