Schwartz, Y; Raslan, R; Mumovic, D; (2015) Multi-Objective Genetic Algorithms for the minimisation of the Life Cycle Carbon Footprint and Life Cycle Cost of the refurbishment of a residential complex's envelope: A case study. In: Samuelson, H and Bhooshan, S and Goldstein, R, (eds.) SimAUD '15: Proceedings of the Symposium on Simulation for Architecture & Urban Design. (pp. pp. 189-196). Society for Modeling & Simulation International (SCS): Alexandria, VA, USA.

Text MOGA for LCCF and LCC of a refurbshed residential building.pdf Access restricted to UCL open access staff Available under License : See the attached licence file. Download (698kB)

Abstract

Life Cycle Analysis (LCA) is an environmental assessment and management framework that aims to simplify the decision-making processes of manufacturing and consumption, with regard to their environmental impact. In the built environment, LCA is often used as a comparative tool that helps in choosing one design alternative over another. Most LCA studies compare a limited number of design alternatives due to the complexity of the method. The main goal of this study is to examine the various Life Cycle aspects of a refurbishment of a case study, and explore the potential of using Multi Objective Genetic Algorithms (MOGA) with Dynamic Thermal Simulation Tool (EnergyPlus) to find optimal refurbishment measures in terms of Life Cycle Carbon Footprint (LCCF) and Life Cycle Cost (LCC) over an assumed life span of 60 years. Results show that MOGA successfully identified optimal design solutions, when taking into account both basic design aspects such as window-to-wall ratio or envelope build-ups, but also more detailed ones, such as thermal bridges insulation and the use of different fuel types for energy generation.

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