An interactive genetic algorithm for portfolio optimization considering the decision maker's preference. Issue 4 (19th May 2018) - Sasaki, Masato; Laamrani, Anas; Yamashiro, Mitsuo
Abstract: Generally, investor has his/her own preference toward risk and return. To develop a decision support system, it should be designed to reflect the investor's preference structure. An Interactive Genetic Algorithm (iGA) is an advanced genetic algorithm method that reflect the decision maker's subjective preference structure. We propose a method for supporting investor's judgement based on portfolio optimization using iGA that present the best compromised solution set that satisfy Pareto optimality and investor's subjective preference structures toward risk and/or return. We develop a system that present investment plan for the investors and show an example to apply the system to the real world problems.