Distributed optimization with population dynamics
Distributed optimization problems are generally described as the minimization of a global objective function in a system, where each agent can get information only from a neighborhood defined by a network topology. To solve this problem, we present a local strategy based on population dynamics, wher...
- Autores:
-
Pantoja Bucheli, Andrés Darío
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2012
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/11882
- Acceso en línea:
- http://hdl.handle.net/1992/11882
- Palabra clave:
- Distribución de energía eléctrica
Densidad eléctrica
Sistemas de energía eléctrica
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
| Summary: | Distributed optimization problems are generally described as the minimization of a global objective function in a system, where each agent can get information only from a neighborhood defined by a network topology. To solve this problem, we present a local strategy based on population dynamics, where payoff functions and tasks are assigned to each node in a connected graph. We prove that the local replicator equation (LRE) converges to an optimal global outcome by means of the local-information exchange subject to the topological constraints of the graph. To show the application of the proposed strategy, we implement the LRE to solve both an economic dispatch and a distributed lighting control problem, requiring variations of the original framework. Finally, we present some simulation and implementation results that illustrate the theoretic optimality and stability of the equilibrium points. |
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