TY - GEN
T1 - Neutrosophic-AHP-based GA Model for Renewals Planning of Hospital Building Assets
AU - Ahmed, Reem
AU - Nasiri, Fuzhan
AU - Zayed, Tarek
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/8
Y1 - 2020/11/8
N2 - Healthcare building infrastructure in Canada is currently facing two problems: Aging and Deferred Maintenance, leading to an increase in unexpected failures causing interruptions in the hospital operation which in turn affects the health and safety of its occupants. Despite the efforts exerted to overcome this, solutions cannot be easily implemented as they are often faced with limited and insufficient funds. Therefore, previous researches have experimented ways targeting a reduction in the rehabilitation costs while sustaining an acceptable physical condition of hospital assets. However, there is more to a building's performance than its physical condition. Hence, this study assesses the hospital performance by including functional parameters of components rather than solely evaluating their physical condition on the basis of an integration between Neutrosophic Logic and Analytic Hierarchy Process, and accordingly improves the rehabilitation decisions by utilizing the output from the previous model as an objective for a genetic algorithm optimization model to prioritize rehabilitation activities within a limited funding allowance. The developed model was validated by applying it to a real hospital situation where the results obtained from the model were compared to the actual output attained from rehabilitation works inside the hospital facility, and the model developed in this study outperformed the current practice by an improvement of 34%. This framework is expected to aid decision-makers in efficiently allocating rehabilitation funds to the most critical hospital building systems which in turn improves the performance and availability of hospital assets.
AB - Healthcare building infrastructure in Canada is currently facing two problems: Aging and Deferred Maintenance, leading to an increase in unexpected failures causing interruptions in the hospital operation which in turn affects the health and safety of its occupants. Despite the efforts exerted to overcome this, solutions cannot be easily implemented as they are often faced with limited and insufficient funds. Therefore, previous researches have experimented ways targeting a reduction in the rehabilitation costs while sustaining an acceptable physical condition of hospital assets. However, there is more to a building's performance than its physical condition. Hence, this study assesses the hospital performance by including functional parameters of components rather than solely evaluating their physical condition on the basis of an integration between Neutrosophic Logic and Analytic Hierarchy Process, and accordingly improves the rehabilitation decisions by utilizing the output from the previous model as an objective for a genetic algorithm optimization model to prioritize rehabilitation activities within a limited funding allowance. The developed model was validated by applying it to a real hospital situation where the results obtained from the model were compared to the actual output attained from rehabilitation works inside the hospital facility, and the model developed in this study outperformed the current practice by an improvement of 34%. This framework is expected to aid decision-makers in efficiently allocating rehabilitation funds to the most critical hospital building systems which in turn improves the performance and availability of hospital assets.
KW - Analytic Hierarchy Process
KW - Genetic Algorithm
KW - Healthcare Facilities
KW - Neutrosophic Logic
KW - Renewals Optimization
UR - http://www.scopus.com/inward/record.url?scp=85100558893&partnerID=8YFLogxK
U2 - 10.1109/DASA51403.2020.9317119
DO - 10.1109/DASA51403.2020.9317119
M3 - Conference article published in proceeding or book
AN - SCOPUS:85100558893
T3 - 2020 International Conference on Decision Aid Sciences and Application, DASA 2020
SP - 1
EP - 5
BT - 2020 International Conference on Decision Aid Sciences and Application, DASA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Decision Aid Sciences and Application, DASA 2020
Y2 - 7 November 2020 through 9 November 2020
ER -