Cyber-Physical Systems (CPS) are increasingly complex and frequently
integrated into modern societies via critical infrastructure systems, products,
and services. Consequently, there is a need for reliable functionality of these
complex systems under various scenarios, from physical failures due to aging,
through to cyber attacks. Indeed, the development of effective strategies to
restore disrupted infrastructure systems continues to be a major challenge.
Hitherto, there have been an increasing number of papers evaluating
cyber-physical infrastructures, yet a comprehensive review focusing on
mathematical modeling and different optimization methods is still lacking.
Thus, this review paper appraises the literature on optimization techniques for
CPS facing disruption, to synthesize key findings on the current methods in
this domain. A total of 108 relevant research papers are reviewed following an
extensive assessment of all major scientific databases. The main mathematical
modeling practices and optimization methods are identified for both
deterministic and stochastic formulations, categorizing them based on the
solution approach (exact, heuristic, meta-heuristic), objective function, and
network size. We also perform keyword clustering and bibliographic coupling
analyses to summarize the current research trends. Future research needs in
terms of the scalability of optimization algorithms are discussed. Overall,
there is a need to shift towards more scalable optimization solution
algorithms, empowered by data-driven methods and machine learning, to provide
reliable decision-support systems for decision-makers and practitioners