To achieve burdening optimization of high-precision copper strips, a model for burdening optimization is
established on the principle of the actual burdening, including cutting down cost, reducing metal burn-up, reusing old copper
stuff, meeting the demand of substitutive degree of kinds of old copper stuff and so on. The model is converted by using
Lagrangian relaxation method. For the model of burdening optimization, a solving method based on non-dominated sorting
genetic algorithm Ⅱ(NSGAⅡ) algorithm is designed and the research is focused on chromosome representation, comparison
operators and the method of sorting Pareto solutions based on fuzzy set theory. The results show that the proposed algorithm
can obtain better solutions compared to existing burdening algorithm to solve the model, and it provides the variety of
possible options.