This article introduces an innovative fuzzy-based approach for developing a comprehensive portfolio optimization model that effectively accounts for inherent uncertainty while incorporating the investor's unique perspective on the dynamic stock market. The multi-objective optimization framework employs Conditional Drawdown at Risk to enhance investor flexibility in determining risk tolerance and optimal investment strategies tailored to specific needs. The research is notable for its pioneering use of intelligent methods to systematically collect valuable data from the Tehran Stock Exchange under fuzzy uncertainty. It incorporates important constraints such as cardinality and ceiling and floor limits for each investment period, allowing for a detailed analysis of various stock market scenarios and potential future outcomes. A case study is conducted with 25 diverse assets from the top five industry groups based on profit per share, from which five shares are thoughtfully selected to effectively demonstrate the model's unique effectiveness. The analysis rigorously assesses the model's performance in real-world conditions, highlighting the importance of accurately understanding the current stock market outlook and trends. To validate the model, the research compares results with a portfolio constructed under similar conditions of certainty and risk. The findings indicate that portfolios created under certainty yield significantly higher values, suggesting that successful portfolio construction is heavily influenced by the prevailing market conditions experienced by investors.