Based on Particle Swarm Optimization Algorithm for Finding Ideal and Effective Solution of Dynamic Batch Reactor Multi-objective Optimization

Abstract

Chemical production process integration is higher and higher, the operation is more and more complex. Based on the dynamic simulation of the process, analysis automation engineering and obtain decision, is beneficial to improve the production efficiency, also ensure safety. The mathematical model is a multi-objective dynamic optimization problem, and it is difficult to solve the multi-objective and it involves the numerical solution of differential system. The particle swarm algorithm strategy is given in this paper for the problem of a numerical solution. Penalty term was added to the PSO algorithm is put forward, as well as the local extremum and global extremum was used to adjust further, so that PSO algorithm is suitable for finding the ideal efficient solutions for multi-objective optimization problem, at the same time in the process of evolution, embedded Runge-Kutta method, the algorithm could been used for dynamic multi-objective optimization problems.