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Credit Optimization Algorithm for Calculating LEED Costs

Authors: Jae-Yong Park; Sul-Geon Choi; Da-Kyung Kim; Min-Chul Jeong; Jung-Sik Kong;

Credit Optimization Algorithm for Calculating LEED Costs

Abstract

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.

Related Organizations
Keywords

certification, Environmental effects of industries and plants, green building; LEED; credit; building energy; certification; LEED cost, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, LEED cost, green building, LEED, GE1-350, building energy, credit

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Top 10%
gold