Artificial bee colony algorithm for real estate portfolio optimization based on risk preference coefficient

Optimization of real estate portfolio is to select two or more different types of real estate for investment, and the previous models based on expected return-variance cannot meet the needs of the investors. Furthermore, the investors change their risk preference with the risk level. In this study, firstly, the semi-variance model of real estate investment portfolio based on risk preference coefficient was constructed. The return per unit of risk is the key factor to determine an investment decision. Secondly, artificial bee colony algorithm (ABC) was employed to solve the constructed model. Finally, a real-world case was analyzed to verify the performance of ABC. The result indicated that ABC could generate better solution than GA and it could be regarded as a useful approach for solving real estate portfolio problem.