Credit Optimization Algorithm for Calculating LEED Costs
As environmental and energy issues continue to emerge as global concerns, Leadership in Energy and Environmental Design (LEED) certification is becoming highly valued. However, since additional costs for LEED certification cannot be estimated before proceeding with certification projects, financial...
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doaj-cb4d17f171c6481ab45e2a4d4c95ee212020-11-25T00:29:48ZengMDPI AGSustainability2071-10502017-09-0199160710.3390/su9091607su9091607Credit Optimization Algorithm for Calculating LEED CostsJae-Yong Park0Sul-Geon Choi1Da-Kyung Kim2Min-Chul Jeong3Jung-Sik Kong4Graduate School of Civil, Environment and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, KoreaDepartment of Architecture, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, KoreaEcolead Corporation, 329 Hangang-daero, Yongsan-gu, Seoul, 04320, KoreaGlobal Loss Control Center, Ph.D., 11th Fl., Samsung Fire & Marine Insurance Co., Ltd., 29 Eulji-ro, Jung-gu, Seoul 04523, KoreaFaculty of Civil, Environment and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu 02841, KoreaAs environmental and energy issues continue to emerge as global concerns, Leadership in Energy and Environmental Design (LEED) certification is becoming highly valued. However, since additional costs for LEED certification cannot be estimated before proceeding with certification projects, financial losses are often incurred. Additional construction costs are the most significant issue faced by enterprises aiming for LEED certification. Rough estimates of the range of additional construction costs are available, but it is difficult to identify factors that increase or decrease the price of a building. Thus, there is a need for a program that provides average data for LEED certification costs and suggests the easiest way to attain credits for a building. Considering that LEED certification is a rating system, this study develops an optimization algorithm that aims to derive the minimum score for a desired LEED level at minimal cost. Credits are studied and classified by their difficulty and the required cost, allowing for an algorithm that can suggest a customized approach to acquire the minimal required score. The practical, data-driven program developed herein helps shorten the consulting process and increases the accessibility of LEED certification.https://www.mdpi.com/2071-1050/9/9/1607green buildingLEEDcreditbuilding energycertificationLEED cost |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jae-Yong Park Sul-Geon Choi Da-Kyung Kim Min-Chul Jeong Jung-Sik Kong |
spellingShingle |
Jae-Yong Park Sul-Geon Choi Da-Kyung Kim Min-Chul Jeong Jung-Sik Kong Credit Optimization Algorithm for Calculating LEED Costs Sustainability green building LEED credit building energy certification LEED cost |
author_facet |
Jae-Yong Park Sul-Geon Choi Da-Kyung Kim Min-Chul Jeong Jung-Sik Kong |
author_sort |
Jae-Yong Park |
title |
Credit Optimization Algorithm for Calculating LEED Costs |
title_short |
Credit Optimization Algorithm for Calculating LEED Costs |
title_full |
Credit Optimization Algorithm for Calculating LEED Costs |
title_fullStr |
Credit Optimization Algorithm for Calculating LEED Costs |
title_full_unstemmed |
Credit Optimization Algorithm for Calculating LEED Costs |
title_sort |
credit optimization algorithm for calculating leed costs |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2017-09-01 |
description |
As environmental and energy issues continue to emerge as global concerns, Leadership in Energy and Environmental Design (LEED) certification is becoming highly valued. However, since additional costs for LEED certification cannot be estimated before proceeding with certification projects, financial losses are often incurred. Additional construction costs are the most significant issue faced by enterprises aiming for LEED certification. Rough estimates of the range of additional construction costs are available, but it is difficult to identify factors that increase or decrease the price of a building. Thus, there is a need for a program that provides average data for LEED certification costs and suggests the easiest way to attain credits for a building. Considering that LEED certification is a rating system, this study develops an optimization algorithm that aims to derive the minimum score for a desired LEED level at minimal cost. Credits are studied and classified by their difficulty and the required cost, allowing for an algorithm that can suggest a customized approach to acquire the minimal required score. The practical, data-driven program developed herein helps shorten the consulting process and increases the accessibility of LEED certification. |
topic |
green building LEED credit building energy certification LEED cost |
url |
https://www.mdpi.com/2071-1050/9/9/1607 |
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