Artículo
A multi-objective interactive dynamic particle swarm optimizer
Autor/es | Barba González, Cristóbal
Nebro, Antonio J. García Nieto, José Manuel Aldana Montes, José F. |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2020 |
Fecha de depósito | 2021-05-20 |
Publicado en |
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Resumen | Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized
simulta-neously. When the objectives change somehow with time, the problems become dynamic, and if the ... Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized simulta-neously. When the objectives change somehow with time, the problems become dynamic, and if the decision maker indicates preferences at runtime, then the algorithms to solve them become interactive. In this paper, we propose the integration of SMPSO/RP, an interactive multi-objective particle swarm optimizer based on SMPSO, with InDM2, an algorithmic template for dynamic interactive optimization with metaheuristics. The result is SMPSO/RPD, an algorithm that provides the search capabilities of SMPSO, incorporates an interactive preference articulation mechanism based on defining one or more reference points, and is able to deal with dynamic problems. We conduct a qualitative study showing the working of SMPSO/RPD on three benchmark problems, remaining a qualitative analysis as an open line of future research. |
Agencias financiadoras | Ministerio de Educación y Ciencia (MEC). España |
Identificador del proyecto | TIN2017-86049-R |
Cita | Barba González, C., Nebro, A.J., García Nieto, J.M. y Aldana Montes, J.F. (2020). A multi-objective interactive dynamic particle swarm optimizer. Progress in Artificial Intelligence, 9 (1), 55-65. |
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