Optimization of schedule with multi-objective for tandem cold rolling mill based on IAGA

To tackle the multi-objective problem in the process of tandem cold rolling, a mathematical model of multi-object optimization is presented. Taking equal relatively power and prevent slippage as objective functions. Aiming to the problem of Standard Genetic Algorithm (SGA), such as premature convergence, oscillation and over-randomization in iterative process, an Improved Adaptive Genetic Algorithm (IAGA) is applied to optimize the system. The algorithm decides the crossover rate and mutation rate of chromosome based on individual adaptive value in calculation process, make the start phase mutate obviously and later phase stable slowly and ensure the population development, seeking balance and entire convergence. Simulated results show that, in comparison with the actual rolling schedule, the optimization rolling schedule makes the reasonable distribution of tandem cold rolling power, gives the full play to equipment capacity, reduces the rate of slippage, improves the product quality, and the proposed method is demonstrated to be competent.