Automated decision support system for optimizing the selection of green building measures

Moatassem Abdallah, Khaled A El-Rayes, Liang Y Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Buildings in the United States account for 72% of electricity consumption, 40% of energy consumption, 13% of water consumption, 39% of carbon footprint, and 30% of waste output. In order to minimize these negative environmental impacts, many public and private owners are requesting that their buildings be more sustainable and certified under the widely known programs such as leadership in energy and environmental design for existing buildings (LEED-EB). To accomplish this, buildings are increasingly integrating green building measures including energy efficient lighting, motion sensors, thermal pane glass, geothermal heat pumps, EnergyStar rated HVAC systems, photovoltaic systems, and wind turbines. This research paper presents the development of an automated decision support system (DSS) that is designed to optimize the selection of green building measures which can be used to upgrade existing buildings. The developed DSS incorporates two optimization models that are capable of (i) minimizing the total upgrade costs required to accomplish a specified LEED-EB certification level such as silver or gold; and (ii) maximizing the number of accredited LEED-EB points within a specified budget of upgrade costs. The DSS is designed to identify a set of optimal upgrade decisions that accomplishes these two optimization objectives. An application example is used to illustrate the capabilities of the DSS and to validate its result.

Original languageEnglish (US)
Title of host publicationISARC 2013 - 30th International Symposium on Automation and Robotics in Construction and Mining, Held in Conjunction with the 23rd World Mining Congress
Pages1326-1333
Number of pages8
StatePublished - 2013
Event30th International Symposium on Automation and Robotics in Construction and Mining, ISARC 2013, Held in Conjunction with the 23rd World Mining Congress - Montreal, QC, Canada
Duration: Aug 11 2013Aug 15 2013

Other

Other30th International Symposium on Automation and Robotics in Construction and Mining, ISARC 2013, Held in Conjunction with the 23rd World Mining Congress
CountryCanada
CityMontreal, QC
Period8/11/138/15/13

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Keywords

  • LEED-EB certification
  • Maximizing building sustainability
  • Optimizing sustainability decisions

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Geotechnical Engineering and Engineering Geology
  • Civil and Structural Engineering

Cite this

Abdallah, M., El-Rayes, K. A., & Liu, L. Y. (2013). Automated decision support system for optimizing the selection of green building measures. In ISARC 2013 - 30th International Symposium on Automation and Robotics in Construction and Mining, Held in Conjunction with the 23rd World Mining Congress (pp. 1326-1333)