A methodology and decision support system for scheduling inspections in a bridge network following a natural disaster

Kepaptsoglou, K; Karlaftis, MG; Bitsikas, T; Panetsos, P; Lambropoulos, S

dc.contributor.author	Kepaptsoglou, K	en
dc.contributor.author	Karlaftis, MG	en
dc.contributor.author	Bitsikas, T	en
dc.contributor.author	Panetsos, P	en
dc.contributor.author	Lambropoulos, S	en
dc.date.accessioned	2014-03-01T02:50:17Z
dc.date.available	2014-03-01T02:50:17Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35036
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-56749149999&partnerID=40&md5=1a6070bcbcf0b7e02359bc5aad2ad78c	en
dc.subject.other	Accidents	en
dc.subject.other	Administrative data processing	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Bridges	en
dc.subject.other	Computer networks	en
dc.subject.other	Computer systems	en
dc.subject.other	Damage detection	en
dc.subject.other	Decision making	en
dc.subject.other	Decision support systems	en
dc.subject.other	Decision theory	en
dc.subject.other	Disasters	en
dc.subject.other	Earthquakes	en
dc.subject.other	Graphical user interfaces	en
dc.subject.other	Heuristic algorithms	en
dc.subject.other	Heuristic methods	en
dc.subject.other	Highway administration	en
dc.subject.other	Highway systems	en
dc.subject.other	Inspection	en
dc.subject.other	Life cycle	en
dc.subject.other	Local area networks	en
dc.subject.other	Maintainability	en
dc.subject.other	Maintenance	en
dc.subject.other	Management	en
dc.subject.other	Management information systems	en
dc.subject.other	Motor transportation	en
dc.subject.other	Probability density function	en
dc.subject.other	Restoration	en
dc.subject.other	Roads and streets	en
dc.subject.other	Scheduling	en
dc.subject.other	Seismology	en
dc.subject.other	Traffic control	en
dc.subject.other	Traffic surveys	en
dc.subject.other	Bridge collapses	en
dc.subject.other	Bridge inspections	en
dc.subject.other	Bridge management systems	en
dc.subject.other	Bridge networks	en
dc.subject.other	Catastrophic events	en
dc.subject.other	Complex constructions	en
dc.subject.other	Critical elements	en
dc.subject.other	Decision supports	en
dc.subject.other	Emergency responses	en
dc.subject.other	Fire departments	en
dc.subject.other	Heuristic procedures	en
dc.subject.other	Highway operations	en
dc.subject.other	Inspection times	en
dc.subject.other	Local authorities	en
dc.subject.other	Natural disasters	en
dc.subject.other	Natural hazards	en
dc.subject.other	Network links	en
dc.subject.other	Road networks	en
dc.subject.other	Transportation infrastructures	en
dc.subject.other	Transportation networks	en
dc.subject.other	Travel speeds	en
dc.subject.other	Travel times	en
dc.subject.other	Freight transportation	en
dc.title	A methodology and decision support system for scheduling inspections in a bridge network following a natural disaster	en
heal.type	conferenceItem	en
heal.publicationDate	2006	en
heal.abstract	Transportation networks are the backbone of modern societies; commuting, freight transportation, leisure travel are mainly accommodated by highways. A natural disaster may disrupt highway operations and therefore multiple community functions, which have to be rapidly restored. In addition, it creates needs for immediate emergency response (relief services etc). It is a fact that transportation networks are ""lifelines""; both emergency response and quick restoration of community functions rely heavily on the ability of transportation networks to handle traffic. Unfortunately, transportation infrastructure elements such as bridges and tunnels are highly prone to damages caused by natural disasters (for example earthquakes). Bridges are probably among the most expensive and complex constructions of a transportation network. On the other hand, bridges are vital links within a transportation network; their failure to operate may lead to long bypasses and inability to access communities. Following a natural hazard, the condition of the transportation network elements must be assessed and damages have to be identified. Inspections are therefore necessary, immediately after the catastrophic event. Specialized crews must be dispatched and inspect critical elements of transportation infrastructure such as bridges. The objective of the current paper is the scheduling of bridge inspection crews following an earthquake. A model and a decision support system, parts of a bridge management system currently developed in Greece are presented, which are designed to aid local authorities in optimally assigning inspectors to the bridge network. The procedure followed for scheduling inspections consists of two major steps: • Identifying the area affected by the earthquake, using a special software package. • Assigning inspection crews to the bridges included within that area, taking into account initial reports on probable network link failure (bridge collapses, pavement failures etc). A brief description of the procedure has as follows: After establishing the area affected by the earthquake and the corresponding part of the transportation network, reports are gathered from the local authorities (police, fire department etc) on possible failures of transportation elements. These reports provide information on possible network links that cannot be crossed by inspection crews. According to that information a new plasmatic network is formed (having bridges as nodes) that takes into account possible access difficulties. Availability of crews and the point within the area where the inspection crews start from are also defined. The decision support system already incorporates estimates on travel times between bridges and bridge inspection times. Using a heuristic procedure (Clarke - Wright ""savings"" algorithm), crews are optimally dispatched to bridges. The decision support system (DSS) is incorporated to a BMS under development for a Greek Motorway Authority (Egnatia Motorway Authority, www.egnatia.gr). All information on the original network (the road network structure and positions of bridges) is stored in the BMS database. Additional information stored is related to the inspection time estimates for each bridge. Other information pre-included concerns the possible starting positions of inspection crews. Data imported directly by the agency include (a) average travel speeds, (b) the number of crews available, (c) the starting point, (d) the part of the network affected by the earthquake and (e) possible failures in network links through a graphical user interface. The DSS transforms the network and provides the necessary results using the ""savings"" heuristic. The results include the bridges that have to be visited by each inspection crew and the total time needed by each crew for inspecting its assigned set of bridges. Inspection of bridges following an earthquake is vital for the quick restoration of the transportation network. The current study presents a methodology and a corresponding decision support system that can facilitate agencies in quickly scheduling emergency aftershock inspections. The tool is based upon accurate estimates on affected transportation regions and a widely used algorithm scheduling. The decision support system is currently in use by the Egnatia Motorway Authority in Greece. © 2006 Taylor & Francis Group.	en
heal.journalName	Proceedings of the 3rd International Conference on Bridge Maintenance, Safety and Management - Bridge Maintenance, Safety, Management, Life-Cycle Performance and Cost	en
dc.identifier.spage	419	en
dc.identifier.epage	420	en