Study on Optimization of Chemical Process Based on Intelligent Computing - Ting Li (Chemical engineering transactions, 2017)
In order to solve the problem that the traditional optimization algorithm cannot calculate the optimal solution, this paper proposes an improved intelligent algorithm to get the optimal solution. Artificial fish swarm algorithm (AFSA) is a new research direction of intelligent optimization algorithm, which provides a new theory and new idea for the optimization of complex chemical process. This subject is based on the basic artificial fish swarm algorithm (AFSA). First, the parameters and disadvantages of the algorithm are analyzed, and an improved artificial fish swarm algorithm (IAFSA) that automatically acquires visual perception ranges and steps is proposed. Then, on the basis of several classic test functions, IAFSA's practicality and stability are proven. Finally, IAFSA is applied to the process optimization of the heat transfer pipe network and the optimization of the T alkylation process to verify the practicability of the algorithm in the actual chemical process.