Abstract
The mathematical model of portfolio optimization has been largely written in terms of minimizing the risk, given the return. The difficulty of this model is to deal with the quadratic programming model due to Markowitz. This situation has been overcome by the recent progress in algorithmic research, and the introduction of linear risk function. This paper deals with the portfolio selection problem with minimum transaction lots. A neighbourhood search algorithm based on active constrained strategy is proposed to solve the mixed integer programming model. The algorithm starts from the solution of the relaxed problem to find a solution which is close to the continuous solution.
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