A Hybrid Algorithm Based on Genetic Algorithm and Simulated Annealing for Solving Portfolio Problem

Abstract

A hybrid algorithm is proposed based on genetic algorithm and simulated annealing for solving portfolio investment with probability criterion. Series structure and parallel structure are adopted by simulated annealing and genetic algorithm respectively. A hybrid algorithm is proposed for which generic algorithm is provided as the main frame of the parallel search, and simulated annealing is used in the mutation process of genetic algorithm. The hybrid algorithm holds the series-parallel structure, which enhance its ability to obtain the optimal solution in the whole solution space. The procedure of hybrid algorithm is described in detail. A case investigation shows that the hybrid algorithm is more feasible and effective by comparison with genetic algorithm. The proposed hybrid algorithm provides investors an applicable method to solve the portfolio problem.