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A multi-objective interactive dynamic particle swarm optimizer

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Abstract

Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized simultaneously. 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.

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Notes

  1. jMetalSP: https://github.com/jMetal/jMetalSP.git.

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Authors and Affiliations

  1. Departamento de Lenguajes y Ciencias de la Computación, Universidad de Málaga, Bulevar Louis Pasteur 35, 29071, Málaga, Spain

    Cristóbal Barba-González, Antonio J. Nebro, José García-Nieto & José F. Aldana-Montes

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  1. Cristóbal Barba-González
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  2. Antonio J. Nebro
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  3. José García-Nieto
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  4. José F. Aldana-Montes
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Correspondence to José García-Nieto.

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This work has been partially funded by Spanish Grants TIN2017-86049-R (Spanish Ministry of Education and Science). Cristóbal Barba-González is supported by Grant BES-2015-072209 (Spanish Ministry of Economy and Competitiveness). José García-Nieto is the recipient of a Post-Doctoral fellowship of “Captación de Talento para la Investigación” Plan Propio at Universidad de Málaga.

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Barba-González, C., Nebro, A.J., García-Nieto, J. et al. A multi-objective interactive dynamic particle swarm optimizer. Prog Artif Intell 9, 55–65 (2020). https://doi.org/10.1007/s13748-019-00198-8

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