Optimization Model and Algorithm for Ingredient Optimization of Copper Strip Production

Ingredient optimization directly affects the quality of copper strip products and production cost. A multiobjective optimization model with the objectives of minimizing raw material cost and deviation of the target ingredient of alloying elements was established by considering the feeding volume limit, inventory, impurity content and alloying element ingredient constraints. A modified non-dominated sorting genetic algorithm II (NSGA-II) is designed to solve the model. The validity of NSGA-II is verified by experiments. The results show that NSGA-II can effectively solve the multi-objective optimization model and provide satisfactory Pareto solution set.