Abstract：It is difficult to determine the weights of the comprehensive objective function in the multi-objective optimization. By both defining and quantifying of preference, 6 classes of preference functions were constructed by using numerical method, and a mathematics model of physical programming was proposed. Physical programming based on genetic algorithm has provided a more flexible and suitable interactive multi-objective optimization algorithm for engineers. Combining with multi-objective rolling schedules in a tandem cold rolling, in the optimization process of rolling schedules, the power distribution, the rolling energy consumption, and the slip factor were selected as objective functions. Physical programming based on genetic algorithm was applied to optimize. The results show that the optimized rolling schedule is better in realizing balance of each stand power, reducing the probability of the scratch, and greatly improving the surface quality and product quality of the plates.
孙 浩， 杨景明， 车海军. 基于遗传算法的PP及冷连轧轧制规程多目标优化[J]. 钢铁, 2014, 49(9): 55-60.
SUN Hao, YANG Jing-ming, CHE Hai-jun. Genetic Algorithm Based PP and Multi-Objective Optimization of Cold Continuous Rolling Schedules. Iron and Steel, 2014, 49(9): 55-60.
Messac A, Ismail-Yahaya A. Multiobjective robust design using physical programming[J]. Structural and Multidisciplinary Optimization, 2002, 23(5): 357-371.
[2]
Messac A, Ismail-Yahaya A. Multiobjective robust design using physical programming[J]. Structural and Multidisciplinary Optimization, 2002, 23(5): 357-371.
2014, Vol. 49 
