Optimization of Wheel Reprofiling Based on the Improved NSGA-II

Algorithm 1

Improved NSGA-II.

	Step 1: generate a random parent population of size .
	Step 2: create a new population with the proposed selection method.
	Step 3: mix the parents and children together and calculate the objective values.
	Step 4: find the Pareto fronts using nondomination sorting.
	Step 5: calculate the global crowding distance of the individuals.
	Step 6: generate a new parent population with nondomination sorting and the global crowding distance.
	Step 7: if the iteration is larger than the threshold, go to 8; otherwise, go to 2.
	Step 8: find the Pareto fronts using nondomination sorting.