A Hybrid Approach for Solving Dynamic Bi-level Optimization Problems

Authors

  • Eduardo Samaniego
  • Pavel Novoa-Hernández Technical State University of Quevedo, Ecuador. Guest Lecturer at State University of Milagro, Ecuador.

DOI:

https://doi.org/10.13053/cys-22-2-2557

Keywords:

Dynamic Bi-level Optimization, Coevolutionary algorithms, Differential Evolution, Self-adaptation, Hybrid Metaheuristics

Abstract

Several real-life decision scenarios are hierarchical, which are commonly modeled as bi-level optimization problems (BOPs). As other decision scenarios, these problems can be dynamic, that is, some elements of their mathematical model can change over time. This kind of uncertainty imposes an extra level of complexity on the model, since the algorithm needs to find the best bi-level solution over time. Despite the importance of studying these problems, the literature reflects just a few works on dynamic bi-level optimization problems (DBOPs). In this context, this work addresses the solution of DBOPs from the viewpoint of metaheuristic methods. Our hypothesis is that, by hybridizing successful solving approaches from both bi-level and dynamic optimization fields, an effective method for DBOPs can be obtained. In this regard, we propose a hybrid method that combines a coevolutionary approach and a self-adaptive, multipopulation algorithm. Experimental results assert our hypothesis, specially for certain information exchange mechanisms.

Author Biography

Pavel Novoa-Hernández, Technical State University of Quevedo, Ecuador. Guest Lecturer at State University of Milagro, Ecuador.

Pavel Novoa-Hernández es Ingeniero Informático por la Universidad de Holguín (Cuba) desde el 2007, y Máster en Ciencias de la Computación e Inteligencia Artificial por la Universidad Central de Las Villas (Cuba), desde el 2010. En el 2013 obtuvo el grado de Doctor en Informática por la Universidad de Granada (España). Actualmente es Profesor Auxiliar del Dpto. Licenciatura en Matemática, de la Universidad de Holguín. Es miembro de la Asociación Cubana de Reconocimiento de Patrones, y de la Sociedad Cubana de Matemática y Computación. Sus intereses investigativos, relacionados con el área de la Soft Computing, incluyen: problemas dinámicos de optimización, meta-heurísticas, problemas de optimización multi-objetivo, entre otros.

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Published

2018-06-30

Issue

Vol. 22 No. 2 (2018): Thematic Issue on Numerical and Evolutionary Optimization (Guest editors: L. Trujillo, Y. Maldonado, O. Schuetze)

Section

Articles

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