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Authors: Alan Díaz Manríquez ; Gregorio Toscano-Pulido and Ricardo Landa-Becerra

Affiliation: CINVESTAV-Tamaulipas, Mexico

ISBN: 978-989-8425-83-6

Keyword(s): Evolutionary algorithms, Dynamic multiobjective optimization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Evolutionary Multiobjective Optimization ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: A dynamic optimization problem (DOP) may involve two or more functions to be optimized simultaneously, as well as constraints and parameters which can be changed over time, it is essential to have a response approach to react when a change is detected. In the past, several memory-based approaches have been proposed in order to solve single-objective dynamic problems. Such approaches use a long-term memory to store the best known solution found so far before a change in the environment occurs, such that the solutions stored can be used as seeds in subsequent environments. However, when we deal with a Dynamic Multiobjective Problems with a Pareto-based evolutionary approach, it is natural to expect several traded-off solutions at each environment. Hence, it would be prohibitive to incorporate a memory-based methodology into it. In this paper, we propose a viable algorithm to incorporate a long-term memory into evolutionary multiobjective optimization approaches. Results indicate that th e proposed approach is competitive with respect to two previously proposed dynamic multiobjective evolutionary approaches. (More)

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Paper citation in several formats:
Díaz Manríquez, A.; Toscano-Pulido, G. and Landa-Becerra, R. (2011). A LONG-TERM MEMORY APPROACH FOR DYNAMIC MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 333-337. DOI: 10.5220/0003675403330337

@conference{ecta11,
author={Alan Díaz Manríquez. and Gregorio Toscano{-}Pulido. and Ricardo Landa{-}Becerra.},
title={A LONG-TERM MEMORY APPROACH FOR DYNAMIC MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)},
year={2011},
pages={333-337},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003675403330337},
isbn={978-989-8425-83-6},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)
TI - A LONG-TERM MEMORY APPROACH FOR DYNAMIC MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS
SN - 978-989-8425-83-6
AU - Díaz Manríquez, A.
AU - Toscano-Pulido, G.
AU - Landa-Becerra, R.
PY - 2011
SP - 333
EP - 337
DO - 10.5220/0003675403330337

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