Management of risk disasters at local level: Proposal of hyper heuristic approach

Matias A. Valenzuela, Alvaro Pena-Fritz, BRODERICK CRAWFORD LABRIN, RICARDO JAVIER SOTO DE GIORGIS

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Under the framework of South American Council of Infrastructure and Planning (Cosiplan-IIRSA in Spanish) project, related on the management of hazard and risk on regional infrastructure (South America), it is presented a new methodology for the identification of vulnerabilities on the infrastructure and their hazards. The Chilean methodology Management of Risk Disasters at Local level (GRDR in Spanish) provides an early detection with low cost of the potential risk on the infrastructure, considering experts and local team, using a data base of the pathologies of the infrastructure and an early warning related with service and extreme event conditions. This paper presents the main issues of this methodology and propose an optimization algorithm for the different phases on its implementation using a hyper heuristic approach with a choice function, and weights determined by a meta-heuristic optimization (genetic algorithm).

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
EditorsVictor Olu Matthews, Adewole Adewumi, Sanjay Misr
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509046423
DOIs
StatePublished - 28 Nov 2017
Event2017 IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017 - Lagos, Nigeria
Duration: 29 Oct 201731 Oct 2017

Publication series

NameProceedings of the IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
Country/TerritoryNigeria
CityLagos
Period29/10/1731/10/17

Keywords

  • choice function
  • hyper-heuristic
  • optimization
  • risk infrastructure
  • risk management

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