Hybridizing an immune artificial algorithm with epsilon constrained method

In this paper, we present a modified version of an algorithm inspired on the T-Cell model, it is an artificial immune system (AIS), based on the process that suffers the T-Cell. The proposed algorithm is called TCEC (T-Cell Epsilon Constrained) due to it is increased with epsilon constrained method,...

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Detalles Bibliográficos
Autores principales: Aragón, Victoria S., Esquivel, Susana Cecilia
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2012
Materias:
Ciencias Informáticas
Algorithms
Hybrid systems
Optimization
Intelligent agents
Artificial Immune System
Constrained Optimization Problem
Epsilon Constrained Method
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23590
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
Descripción
Sumario:In this paper, we present a modified version of an algorithm inspired on the T-Cell model, it is an artificial immune system (AIS), based on the process that suffers the T-Cell. The proposed algorithm is called TCEC (T-Cell Epsilon Constrained) due to it is increased with epsilon constrained method, for solving constrained (numerical) opti- mization problems. We validate our proposed approach with a set of 36 test functions provided for the CEC 2010 competition. We indirectly compare our results with respect to a version of the differential evolution algorithm. Our results show that TCEC can found feasible solutions on almost test functions with 10 and 30 decision variables.

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