Horn, J., Nafpliotis, N., and Goldberg, G. E., “A niched Pareto genetic algorithm for multiobjective optimization, Piscataway,” IEEE Service Center, NJ, pp. 82–87, 1994.

has been cited by the following article:

• TITLE: Finding the Efficient Frontier for a Mixed Integer Portfolio Choice Problem Using a Multiobjective Algorithm

  AUTHORS: K. P. ANAGNOSTOPOULOS, G. MAMANIS

  KEYWORDS: Markowitz Model, Multiobjective Optimization, NSGA, Portfolio Selection

  JOURNAL NAME: iBusiness, Vol.1 No.2, December 18, 2009

  ABSTRACT: We propose a computational procedure to find the efficient frontier for the standard Markowitz mean-variance model with discrete variables. The integer constraints limit on the one hand the portfolio to contain a predetermined number of assets and, on the other hand, the proportion of the portfolio held in a given asset. We adapt the multiobjective algorithm NSGA for solving the problem. The algorithm ranks the solutions of each generation in layers based on Pareto non-domination. We have applied the procedure in sixty assets of ATHEX. We have also compared the algorithm with a single genetic algorithm. The computational results indicate that the procedure is promising for this class of problems.