A novel mathematical multi-criteria decision-making model for optimizing life cycle energy and cost in construction projects planning. (4th March 2023)

• Record Type: Journal Article
• Authors: Giahchy, Saeid; Hosseini, Seyed Azim; Akhbari, Mahdieh; Safa, Ebrahim; Akbarpour, Abbas
• Is Part Of: Architectural engineering and design management. Volume 19:Number 2(2023)
• Page Start: 200
• Page End: 213
• Publication Date: 2023-03-04
• Subjects: Energy efficiency -- Life cycle energy -- Energy-saving -- Construction industry -- Multi-criteria decision-making; Building -- Periodicals; Architectural design -- Periodicals; Construction industry -- Management -- Periodicals; 720
• DOI: 10.1080/17452007.2022.2104207
• Languages: English
• ISSNs: 1745-2007

Abstract

ABSTRACT: Today, energy management systems are usually assessed as key to sustainable development goals. One of the best criteria for energy management systems in construction projects is Life Cycle Energy Analysis (LCEA). This research is a quantitative-qualitative study based on a Multi-Criteria Decision-Making (MCDM) model. This research involves four stages: library study, statistical survey, descriptive study, and case study. The review of previous studies showed that the LCEA and MCDM alone could not provide a comprehensive energy consumption management assessment model, due to inherent uncertainty and the existence of various analysis parameters; however, when are used in an integrated framework; the LCEA & MCDM hybrid approach serves as the best instruments to assess energy management systems. This research has proposed a newly developed hybrid multi-objective mathematical decision-making model to select appropriate and optimum options for all building shell components to optimize and manage the Cost and Energy of the Building Life Cycle. The life cycle energy analysis of an educational building in a case study showed that optimization using the proposed model saves about 16% of energy during the lifetime of the building. In addition, the investment payback period for this optimization is less than seven months in the first year of operation.