Risk-informed decision support for infrastructure network operation - the Complex Distributed Agent Network (CoDAN) framework
This thesis presents a framework for risk-informed decision support for infrastructure networks operation, referred to as the Complex Distributed Agent Network (CoDAN) framework. CoDAN has been designed to recognize and model infrastructure systems as the result of interacting physical, natural, and...
- Autores:
-
Gómez Castro, Camilo Hernando
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2014
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/7819
- Acceso en línea:
- http://hdl.handle.net/1992/7819
- Palabra clave:
- Análisis de sistemas - Investigaciones
Análisis cluster - Investigaciones
Toma de decisiones - Investigaciones
Redes de información - Investigaciones
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
Summary: | This thesis presents a framework for risk-informed decision support for infrastructure networks operation, referred to as the Complex Distributed Agent Network (CoDAN) framework. CoDAN has been designed to recognize and model infrastructure systems as the result of interacting physical, natural, and social systems, and is built upon the following principles: - different decision problems occur at different system description, or resolution, levels; - decentralization schemes respond to each specific system and problem; - control processes are embraced by distributed decision units to maintain and improve network indicators of performance and risk; and - socio-economic and organizational aspects affect infrastructure performance as much as technical aspects. To operationalize the stated principles, CoDAN is comprised of the three following phases: - Phase I ("Knowing the system") explores network properties (e.g., relative importance of network components) and embraces a human-machine interactive process to define relevant sub-systems in the context of a decision problem, supported on supervised and unsupervised clustering algorithms; - Phase II ("Who's in charge") develops resource allocation models in terms of subsystems, signaling which of those are appropriate for autonomous use of resources in the context of problems such as maintenance or disaster relief throughout the network; - Phase III ("Behavior under control") defines agents associated to key decision problems of autonomous sub-systems, and provides them with the capabilities to control variables of interest (e.g., connectivity, flow reliability) and pursue a target system state |
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