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Fuzzy Monte Carlo simulation optimization for selecting materials in green buildings

    Mohamed Marzouk   Affiliation

Abstract

Global interest in sustainable and green building design has been increasing in the last few decades. This interest is strengthened by the fact that sustainable measures help in reducing negative social and environmental impacts of buildings. For that, this paper aims to develop a mixed integer optimization model that aids architects/designers and owner representatives during design stage in selecting building materials taking into consideration costs and risks that are involved in the selection process. The model is developed as a simulation optimization tool based on the Leadership in Energy and Environmental Design (LEED) rating system for new construction. The developed model allows deterministic and probabilistic cost analysis of various design alternatives. In addition, it identifies the least possible cost to gain the LEED credits and the risks associated with materials’ quantities and materials’ unit prices. To illustrate the use of the proposed tool, a case study of an office building project constructed in Egypt is presented. An integrated Fuzzy Monte Carlo Simulation (FMCS) analysis is performed to account for the associated risks of using new materials in the considered case study. The proposed model is capable to capture the cost uncertainty of building materials and to identify the cost and sustainability performance of various building materials by relating the LEED rating system for new construction.

Keyword : Fuzzy Monte Carlo Simulation, green buildings, LEED, optimization, materials cost, risk management, sustainability

How to Cite
Marzouk, M. . (2020). Fuzzy Monte Carlo simulation optimization for selecting materials in green buildings. Journal of Environmental Engineering and Landscape Management, 28(2), 95-104. https://doi.org/10.3846/jeelm.2020.12087
Published in Issue
Apr 27, 2020
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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