Two mean-variance models are proposed for portofolio selection with fixed transaction costs and minimum lots. The portofolio selection problems are modeled as a non-smooth nonlinear integer programming problem with single objective function and multiple objective functions respectively.
A new genetic algorithm based on NSGA-II is designed to solve the proposed models. It is illustrated via a numerical example that the genetic algorithm can be used to solve portofolio selection problems efficiently in practice.