隨著營建企業多元化經營的發展，有效地運用資金已成為企業經營的重要策略，其中透過證券之投資組合管理，使資金的運用能降低風險提高報酬乃成為主要的經營課題。證券投資組合管理主要運用多元化投資原則，選擇相關性低的投資標的，分配各股比重決定此組合的效益以分散風險。
人工智慧應用於證券投資組合的研究中，以往都以基因演算法尋找最佳投資規則但缺乏語意程度的表達，而模糊推論(Fuzzy inference)則需要專家知識庫與經驗法則，但缺乏有系統的規則制定方法，因此有必要結合雙方的優點建立有效的投資模式。
本研究結合基因演算法與模糊理論，發展一套模糊基因最佳化投資系統(Optimize Portfolio Inference Engine,OPIE)，並以此建立預測系統與組合最佳化模式，採用基因演算法最佳化模糊歸屬函以推論報酬率和風險，並搜尋報酬風險多目標的最佳化。
經由模式驗證可知預測漲跌的趨勢甚佳，可用來權衡選取投資組合，其報酬率亦優於基金和大盤表現，提供投資者高報酬低風險的投資選擇，以利營建企業多角化經營，此為本研究整合預測和最佳化的最大貢獻。

Upon the development of diversity industrial environment, the construction industry fund management has become an important strategy. The aim of the application is to reduce the risk and raise the return, it has become a main issue through out the portfolio securities. Portfolio securities use the diversification investment principle by choosing low correlation stock and assign the weights of each stock to determine the benefits of this folio in order to disperse the risk.
From the past, applying the artificial intelligence research portfolio has always been the best solution to calculate the best combination of the stock choices. Lack of language communication has also been known as a big issue. The fuzzy inference requires expert's knowledge and experiences, but systematic has always been the lacking issue. So it is necessary to combine the advantages of both systems to set up effective investment model. This study combine genetic algorithms and fuzzy theory to develop a Fuzzy-GA optimization invest system (Optimize Portfolio Inference Engine, OPIE), thus by establishing a stock predicting system it is possible to apply the system on the folio to calculate fuzzy membership functions. This will not only gives the best capital gain return but it also brings the investment to the lowest risks.
From the simulation, it is possible to predict the trends of the investments, thus by taking this advantage, best return and performance has become possible to achieve. Offering the investors the best solutions to invest will not only bring the industry good returns but it also gives the industry a chance to become a multiple and world wide industry.

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