高科技產業面對產業環境快速變遷，競爭壓力劇增下，產能規劃受到定價策略、成本結構、市場需求、存貨管理與產能限制等因素影響，同時也受限於需求預測的結果，處於被動的情況也限制了企業財務績效的表現，同時高科技產業為資本密集產業，其中以產能建置的設備機台花費支出占大宗，可見產能管理的能力對公司營運目標的達成有非常大的影響。
也因產能管理受到許多因素的影響，需考慮多個目標進行規劃已成趨勢，方能提升整體企業收益；同時，高科技產業之製程也相對其他產業來的複雜，使得其問題規劃擴大，因此本研究提供一決策支援系統來協助決策者釐清決策問題之架構，透過系統介面與互動將整個決策過程外顯化，以引導決策者進行決策方案的選取。
本研究以高科技產業為研究對象，透過紫式決策分析架構，以決策流程為系統建構導向，架構產能規劃之決策支援系統模組，建立一產能規劃決策支援系統。運用基因演算法作為求解核心模組，針對財務績效層面與生產績效層面之目標進行求解，並透過互動模組，針對求解結果進行分析，協助決策者從中選取適當的決策方案。本研究以台灣某半導體公司為實證以檢驗效度，實證結果顯示皆較案例公司之原本規劃較好，同時也能將決策者對於目標方案之偏好透過互動模組外顯出來，進而達到提升決策品質一致性與快速的反應時間。

High-tech industries face rapidly changing of industrial environment and dramatically increasing of the competitive pressure, while capacity planning is affected by pricing strategies, cost structure, market demand, inventory management, capacity portfolio,and demand forecast. Furthermore, high-tech industries are capital-intensive industries, which requires substantial amount of capital for the capacity-building equipment machine. With the industrial environment and its capital-intensive quality, the capacity manage is especially improtant to reaceh operational goals. In order to enhance the overall return, multi-objectives for capacity planning is crutial.
This study imports the concept of capacity management of high-tech industry, using UNISON decision framework to construct capacity planning decision support system for the decision-oriented. The genetic algorithms as the the core module to solve the multi-objectives capacity planning for financial goals and production goal. In the interactive scheme, the decision makers are guided iteratively to the most preferred solution. The decision makers can use the systematic procedure to analyze and to solve the problem to reach the optimal financial goals and production goal. This study applied to semiconductor manufacturing as empirical objects, and the results show our decision support system is better than case corporations and also show the preference of the goal of decision makers through interactive modules, and thus to enhance the consistency of decision-making quality and faster response time.

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