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Decision-making model for sustainable management of Australian community buildings: Combined approach using analytical hierarchy process and neuro-fuzzy system
journal contributionposted on 20.06.2022, 22:49 authored by Pushpitha KalutaraPushpitha Kalutara, Guomin Zhang, Sujeeva Setunge, Ron Wakefield
Community buildings such as childcare/ aged care centres, sports pavilions possesses a massive investment in Australian economy built up over generations. From one viewpoint, they are providing essential services to the community and another viewpoint, the delivery of those services is limited by the ongoing degradation of the structural and service components of buildings, the scarcity of resources and the lack of funding by state and federal governments. This poses a huge challenge to Australian local governments to sustainably manage community buildings accountable to them. Reaching the goal takes further away by the absence of a holistic decision-making model for sustainable management of Australian community buildings. This study approaches the problem holistically identifying the sustainable decisions to be made through triple bottom line (environment, economic and social) and functional aspects. Incorporation of the influencing factors of each aspect led to a comprehensive decision-making structure which was the base for developing an effective decision-making model. The design of the model is based on the combination of two analytical methods namely Analytical Hierarchy Process (AHP) and Neuro Fuzzy System (NFS). The final output of the model computes the sustainability index which interprets the total sustainability impact of a given building component. This enables building asset managers to utilise the index to prioritise the maintenance tasks of all building components. The paper encapsulates the results of a case study to explain the outputs of the model and their practical significance. The study previously conducted two industry-wide questionnaire surveys to finalise the attributes of the decision-making structure and the importance of the attributes (weightings).