Performance-Based Maintenance and Operation of Multi-Campus Critical Infrastructure Facilities Using Supply Chain Multi-Choice Goal Programming

Building maintenance is a critical component of ensuring long-term performance, safety, and cost-efficiency in both conventional and critical infrastructures. While traditional contracting approaches have often led to inefficiencies and rigid procurement systems, recent developments in performance-based maintenance, digital technologies, and multi-objective optimization provide opportunities to enhance both operational reliability and energy performance. From a resilience perspective, the ability to sustain functionality, adapt maintenance intensity, and recover performance under resource or operational stress is essential for ensuring infrastructure continuity and resilience. This study develops and validates an optimization model for the operation and maintenance of large campus infrastructures, addressing the persistent imbalance between over-maintenance, where costs exceed optimal levels by up to 300%, and under-maintenance, which compromises performance continuity and weakens resilience over time. The model integrates maintenance efficiency indicators, building performance indices, and energy-efficiency retrofits, particularly LED-based lighting upgrades, within a multi-choice goal programming framework. Using datasets from 15 campuses comprising over 2000 buildings, the model was tested through case studies, sensitivity analyses, and simulations under varying facility life cycle expectancies. The facilities were analyzed for alternative life cycles of 25, 50, 75, and 90 years, and the design life cycle was set for 50 years. The results show that the optimized approach can reduce maintenance costs by an average of 34%, with savings ranging from 1% to 55% across campuses. Additionally, energy retrofit strategies such as LED replacement yielded significant economic and environmental benefits, with payback periods of approximately 2–2.5 years. The findings demonstrate that integrated maintenance and energy-efficiency planning can simultaneously enhance building performance, reduce costs, and support sustainability objectives, offering a practical decision-support tool for managing large-scale campus infrastructures.

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Publication Details

Journal
Applied Sciences
Published
2025-10-17
DOI
https://doi.org/10.3390/app152011161
Primary Topic
Optimization and Mathematical Programming
Type
article
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article

Performance-Based Maintenance and Operation of Multi-Campus Critical Infrastructure Facilities Using Supply Chain Multi-Choice Goal Programming

S. N. Levi, Igal M. Shohet, Fadi Shahin, Reem Zeibak-Shini
Applied Sciences
Optimization and Mathematical Programming
article

Performance-Based Maintenance and Operation of Multi-Campus Critical Infrastructure Facilities Using Supply Chain Multi-Choice Goal Programming

S. N. Levi, Igal M. Shohet, Fadi Shahin, Reem Zeibak-Shini
article en

Abstract

Building maintenance is a critical component of ensuring long-term performance, safety, and cost-efficiency in both conventional and critical infrastructures. While traditional contracting approaches have often led to inefficiencies and rigid procurement systems, recent developments in performance-based maintenance, digital technologies, and multi-objective optimization provide opportunities to enhance both operational reliability and energy performance. From a resilience perspective, the ability to sustain functionality, adapt maintenance intensity, and recover performance under resource or operational stress is essential for ensuring infrastructure continuity and resilience. This study develops and validates an optimization model for the operation and maintenance of large campus infrastructures, addressing the persistent imbalance between over-maintenance, where costs exceed optimal levels by up to 300%, and under-maintenance, which compromises performance continuity and weakens resilience over time. The model integrates maintenance efficiency indicators, building performance indices, and energy-efficiency retrofits, particularly LED-based lighting upgrades, within a multi-choice goal programming framework. Using datasets from 15 campuses comprising over 2000 buildings, the model was tested through case studies, sensitivity analyses, and simulations under varying facility life cycle expectancies. The facilities were analyzed for alternative life cycles of 25, 50, 75, and 90 years, and the design life cycle was set for 50 years. The results show that the optimized approach can reduce maintenance costs by an average of 34%, with savings ranging from 1% to 55% across campuses. Additionally, energy retrofit strategies such as LED replacement yielded significant economic and environmental benefits, with payback periods of approximately 2–2.5 years. The findings demonstrate that integrated maintenance and energy-efficiency planning can simultaneously enhance building performance, reduce costs, and support sustainability objectives, offering a practical decision-support tool for managing large-scale campus infrastructures.

Applied SciencesVol. 15(20)
Ben-Gurion University of the Negev (IL), Chaoyang University of Technology (TW), Braude College of Engineering Karmiel (IL)
Openalex Percentile: Top 62%
Optimization and Mathematical Programming
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