Optimization schedule for preventing slippage on tandem cold rolling mills based on IAGA

To tackle the problem of slippage during the cold rolling process of a tandem mill, a schedule optimization model for preventing slippage was established based on slip factor. Aiming to the shortages of the standard genetic algorithm, such as premature convergence, oscillation and over-randomization, an improved adaptive genetic algorithm was applied to optimize the system. In the algorithm a population-sorted multi-roulette-wheel selection operator was put forward for reducing the selected error generated by roulette-wheel randomization and promoting the probability of selecting better individuals. Simultaneously the algorithm decides the crossover rate and mutation rate of chromosome based on the individual adaptive value in the calculation process, makes the start phase variable obviously and the later phase stable slowly, and ensures population development, seeking balance and entire convergence. Experimental results and actual application show that the schedule optimization model can reduce the slip probability prominently, improve the product quality, and achieve a better economic benefit.