Dynamic scenario simulation optimization

• Tipo: Tese
• Data: 2006

Autores

André Monteiro de Oliveira Restivo (Autor) FEUP; Luis Paulo Reis (Orientador Técnico) FEUP

Classificação Científica

CORDIS: Ciências Físicas > Ciência de computadores > Cibernética > Inteligência artificial

Instituições Associadas

FEUP - Faculdade de Engenharia da Universidade do Porto

Outras Informações

Abstract (EN): The optimization of parameter driven simulations has been the focus of many research papers. Algorithms like Hill Climbing, Tabu-Search and Simulated Annealing have been thoroughly discussed and analyzed. However, these algorithms do not take into account the fact that simulations can have dynamic scenarios. In this dissertation, the possibility of using the classical optimization methods just mentioned, combined with clustering techniques, in order to optimize parameter driven simulations having dynamic scenarios, will be analyzed. This will be accomplished by optimizing simulations in several random static scenarios. The optimum results of each of these optimizations will be clustered in order to find a set of typical solutions for the simulation. These typical solutions can then be used in dynamic scenario simulations as references that will help the simulation adapt to scenario changes. A generic optimization and clustering system was developed in order to test the method just described. A simple traffic simulation system, to be used as a testbed, was also developed. The results of this approach show that, in some cases, it is possible to improve the outcome of simulations in dynamic environments and still use the classical methods developed for static scenarios.

Idioma: Português

Tipo (Avaliação Docente): Científica

Nº de páginas: 129