Abstract
Natural hazards such as earthquakes, floods and tornadoes can cause extensive failure of critical infrastructures including bridges, water and sewer systems, gas and electricity supply systems, and hospital and communication systems. Following a natural hazard, the condition of structures and critical infrastructures must be assessed and damages have to be identified; inspections are therefore necessary since failure to rapidly inspect and subsequently repair infrastructure elements will delay search and rescue operations and relief efforts. The objective of this work is scheduling structure and infrastructure inspection crews following an earthquake in densely populated metropolitan areas. A model is proposed and a decision support system is designed to aid local authorities in optimally assigning inspectors to critical infrastructures. A combined Particle Swarm - Ant Colony Optimization based framework is developed which proves an instance of a successful application of the philosophy of bounded rationality and decentralized decision-making for solving global optimization problems.
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Plevris, V., Karlaftis, M.G., Lagaros, N.D. (2010). A Swarm Intelligence Approach for Emergency Infrastructure Inspection Scheduling. In: Gopalakrishnan, K., Peeta, S. (eds) Sustainable and Resilient Critical Infrastructure Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11405-2_8
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DOI: https://doi.org/10.1007/978-3-642-11405-2_8
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