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Open AccessArticle

Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm

1
Department of Architecture and Planning, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
2
Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7BA, United Kingdom
*
Author to whom correspondence should be addressed.
Buildings 2020, 10(5), 88; https://doi.org/10.3390/buildings10050088
Received: 26 February 2020 / Revised: 11 April 2020 / Accepted: 15 April 2020 / Published: 7 May 2020
(This article belongs to the Special Issue Building Energy Consumption in the Global South)
Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Köppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case. View Full-Text
Keywords: multi-objective building design optimization; robustness assessment; multi-criteria decision making multi-objective building design optimization; robustness assessment; multi-criteria decision making
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Chaturvedi, S.; Rajasekar, E.; Natarajan, S. Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm. Buildings 2020, 10, 88.

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