Developing a hybrid intelligent system for optimizing syndicated venture capital portfolios

Obviously, financial aspect is the most important pillar of technology development. Furthermore, the role of venture capital in developing small and medium size knowledge-based institutions is vital. However, startup portfolio selection and venture capital firms' syndication have always been critical challenges in VC industry and the need for integrated methods based on sophisticated quantitative techniques are always being felt. In this research, startup portfolio optimization is simulated which is more similar to real world problems rather than other research. In order to attain this goal, preferences of startups as decision-makers and the interaction between investees and investors are considered. Concerning the complexity of the problem, the best-known model to simulate this problem is an agent-based modeling and also by using harmony search algorithm, the optimization procedure is successfully implemented. Through implementing this procedure, not only the portfolio's return on investment is optimized but also venture capital firms' syndication and their share is then determined. Finally, several numerical illustrations are solved using the proposed combinatorial model.