PSO Based Steel Rolling Process Optimization

2011 ◽  
Vol 346 ◽  
pp. 172-178
Author(s):  
Jun Jun Yang ◽  
Jia Chuan Shi ◽  
Wen Zhang ◽  
Li Ping Liang ◽  
Pei Jian Zhao

Based on the analysis of the rolling process in iron and steel enterprises, an optimal load distribution model is established for rolling mills. The objective function is to minimize the total energy consumption. The equipment and process constraints are considered. The particle swarm optimization (PSO) is employed to get the optimal rolling reductions. The simulation of a six-frame strip demonstrates the feasibility of the proposed method in Jinan Iron & Steel Group. The experimental result shows that the proposed method is efficiency in the optimal load distribution problems.

2021 ◽  
Author(s):  
Cao Yuan ◽  
Jianguo Cao ◽  
Wang Tao ◽  
Wang Leilei ◽  
Li Fang ◽  
...  

Abstract Aiming at the problem of load distribution during multi-pass cold rolling of nuclear zirconium alloy strip, the load distribution model with good shape is established by the self-adaptive particle swarm optimization algorithm (SAPSO), considering the main constraint conditions including rolling force, reduction and torque in cold rolling process. Based on the penalty function method transforming the constraint problem into the unconstrained problem, the particle swarm optimization algorithm with adaptive inertia weight factor optimized the load distribution model is developed to improve the local search ability of the particle swarm optimization algorithm. Compared with the existing nuclear zirconium alloy industrial schedule, the simulation results of load distribution based on the SAPSO can keep good shape in multi-pass cold rolling process with the high prediction accuracy. The industrial experiments demonstrate that the proportional crown difference value is consistent, the plate shape flatness is good.


2014 ◽  
Vol 494-495 ◽  
pp. 1715-1718
Author(s):  
Gui Li Yuan ◽  
Tong Yu ◽  
Juan Du

The classic multi-objective optimization method of sub goals multiplication and division theory is applied to solve optimal load distribution problem in thermal power plants. A multi-objective optimization model is built which comprehensively reflects the economy, environmental protection and speediness. The proposed model effectively avoids the target normalization and weights determination existing in the process of changing the multi-objective optimization problem into a single objective optimization problem. Since genetic algorithm (GA) has the drawback of falling into local optimum, adaptive immune vaccines algorithm (AIVA) is applied to optimize the constructed model and the results are compared with that optimized by genetic algorithm. Simulation shows this method can complete multi-objective optimal load distribution quickly and efficiently.


2020 ◽  
Vol 13 (1) ◽  
pp. 114-129 ◽  
Author(s):  
Omar Abdel Wahab ◽  
Jamal Bentahar ◽  
Hadi Otrok ◽  
Azzam Mourad

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