Maximizing the value of residential projects using fuzzy rule based linear programming
Optimizing the allocation of residence types has a great impact on efficient management of resources for construction projects. Hence, determining appropriate allocation of residence types provides effective financial activities, especially for large-scaled residential projects. Subjectivity and vagueness in the determination of price per m2 for residences requires the consideration of fuzzy logic, since the modeling of imprecise and qualitative knowledge, as well as the transmission and handling of uncertainty at various stages are possible through the use of fuzzy sets. This study proposes an approach that integrates Fuzzy Rule Based System (FRBS) with mathematical programming. In the proposed hybrid approach, FRBS is used to set price per square meter and it provides input for Net Present Value (NPV) formulation. Mixed integer linear programming (MILP) model is developed for the maximization of (NPV) of the project. The proposed model is applied to a residential project in Istanbul to demonstrate its performance. The optimal NPVs and allocation results for four types of residences are analyzed depending on the different factor levels of total construction area, sales rate and bank loan interest rate. The results indicate that the optimal NPV and allocation of residences are significantly influenced by the factor of construction area.
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