對於道路瀝青混凝土鋪築工程而言，各項工程之資源及限制條件各有異同，為求得最大收益之成本及如期完工的目標，如何於道路瀝青混凝土鋪築效益之限制條件及需求下，利用線性規劃最佳化模式，而達到最大收益的情形，已為道路瀝青混凝土鋪築工程管理者之重要課題。 本研究針對捷運某區段標工程辦理車站道路瀝青混凝土鋪築效益之最佳化，以提供JV廠商採購瀝青混凝土及鋪築施工為研究範圍，建立一套以整數規劃為架構之數學最佳化模式，協助JV廠商管理人將現有資源配置與整合，統一規劃施工方案，以使衍生之成本最大化增加收益。當外在環境及限制條件改變時，本研究模式可隨時依最新條件調整參數，重新進行新的需求規劃方案。另經由敏感度分析，針對各參數之敏感度變化趨勢，主動調整相關參數，以因應實務變化得調整新的方案。本研究將各案件之基本資料及限制條件訂定各限制式之參數，將資料以EXCEL軟體方式輸入LINGO8.0套裝軟體求解，即可得各案規劃後之成本最佳化之結果。 為驗證模式合理性，以某JV廠商履行捷運某區段標工程辦理車站道路瀝青混凝土鋪築工程之案件為範例測試，並以最佳化模式所求得的最大成本收益方式求出之成本進行比較，以驗證本研究最佳化模式產生的最大收益結果，確實較人工經驗所得成本更低，更有效率。故本研究可靈活運用於先期規劃及檢討等成本規劃問題，以輔助決策者辦理規劃作業重要之參考。 The resources and constraints of road asphalt concrete paving projects vary from case to case. To achieve maximum returns of the costs and the goal of timely completion of projects, how to use the linear planning optimization model to obtain maximum returns under constraints and demands of road asphalt concrete paving efficiency has become an important issue of road asphalt concrete pavement project managers. With efficiency optimization for a MRT station road asphalt concrete paving project as an example, to provide JV industry with a reference in asphalt concrete purchase and paving projects, this study established a mathematical optimization model based on integer programming to help the JV industry to integrate currently available resources to plan the implementation consistently and achieve maximum returns of the costs. When external environment and constraints change, the research model can adjust parameters at any time according to the latest conditions to conduct new demand planning. In addition, by sensitivity analysis, the model can actively adjust relevant parameters according to the sensitivity change trends of various parameters to get new plans in response to practical changes. This study set parameters of various constraints according to basic data and limiting conditions of each case. Data are inputted into LINGO8.0 in the form of EXCEL to obtain the cost optimization results of various cases after planning. To verify the model rationality, this study tested the case of the implementation by a JV manufacturer of an asphalt concrete paving of MRT station road project, and compared with costs obtained using maximum cost returns of the optimization model. It was verified that the optimization model proposed in this study is more efficient and less costly than the experiential one. Hence, the proposed method can be flexibly applied to cost planning problems such as advance planning and review to help decision-makers in planning operations.
