PSO algorithm-based schedule optimization for tandem cold mills

Abstract

The cold rolling production scheduling problem is an extremely difficult process, so it is quite difficult to achieve an optimal solution with traditional optimization methods. Based on rolling feature of continuous tandem cold rolling mill, such as multi-variable, strong coupling, non-linear, this paper presents a Particle Swarm Optimization (PSO) algorithm schedule optimization procedure for tandem cold rolling mills, base to computer powerful data processing capacity. Adopt the power distribution cost function as objective function, make the rolling force, rolling power, rolling torque, speed and other parameters meet certain requirement. Sequential unconstrained minimization technique (SUMT) replaces a constrained optimization problem with a sequence of unconstrained optimization problem. Apply PSO algorithm to optimize the objective function to obtain the optimal solution. It makes the reasonable distribution of tandem cold rolling power, gives full play to equipment capacity and improves the production efficiency.