A Multi-Objective Optimization Model for Advanced Transportation Projects Portfolio Using Goal Programming.

One of the important industries of Iran is advanced transportation, and the lack of optimal project portfolio planning has had a negative impact on its economy and geopolitical position. The study aims to design an optimal portfolio of advanced transportation projects using goal programming (GP) method and Shannon entropy technique. In the study, by implementing six scientific steps in the presented framework, the selection and balance of portfolio projects were carried out to achieve benefits. Considering Iran's geopolitical advantages and the support priorities of the Knowledge-Based Economy Development Headquarters, 30 key projects in the maritime, rail, air, and space fields were identified and evaluated with the criteria of risk, financial return (ROI), probability of success, investment volume, technology maturity, and commercial potential. The weight of the criteria was determined by the Shannon entropy method. By using the goal-oriented programming model and after balancing the portfolio, the actual projects were entered into the final portfolio, and finally a project portfolio road map was drawn for better understanding and management of the portfolio. The designed project portfolio simultaneously covers the short-term goals of tourist vessels, medium-term port smartization, and long-term satellite systems, and creates a good balance between advanced technologies and feasibility. The findings show that this optimal combination can be effective in reducing operating costs by up to 35%, increasing productivity by 40%, and reducing overall project risk by 25%. [ABSTRACT FROM AUTHOR]