DETERMINING REQUIRED HOUSING STOCK BY MONTE CARLO SIMULATION: ISTANBUL CASE STUDY
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2019-10-07
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en
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Abstract
The basis of planning is the idea of creating a 'good' city (Steele and Ruming 2002). Therefore, planning discipline needs to analyze market needs well and create balance with public interest while preparing implementation plans. However, sometimes current practices cannot fully respond to market dynamics and efficiently integrate uncertainties into the system. This situation leads to deficiencies while determining the required stock of urban functions and interpreting the needs. Luckily, it is possible to integrate more parameters into the systems and test many variations. Thus more effective studies can be realized based on these detailed analyses. This thesis examines the integration of many parameters into the system during the planning process. On this purpose, this study explores the development of future based projections for planning decisions by the Monte Carlo Simulation method. It runs the desired repetition in the specified variable range and tests possibilities with nonparametric data sets to determine the housing stock to be needed.
Keywords: Monte Carlo Simulation, Reducing Uncertainties, Urban Planning, Housing Stock
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Faculteit der Managementwetenschappen