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The Influence of Swarm Topologies in Many-Objective Optimization Problems

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Book cover Evolutionary Multi-Criterion Optimization (EMO 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12654))

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Abstract

Particle Swarm Optimization (PSO) is a bio-inspired metaheuristic that has been successfully adopted for single- and multi-objective optimization. Several studies show that the way in which particles are connected with each other (the swarm topology) influences PSO’s behavior. A few of these studies have focused on analyzing the influence of swarm topologies on the performance of Multi-objective Particle Swarm Optimizers (MOPSOs) using problems with two or three objectives. However, to the authors’ best knowledge such studies have not been done so far for many-objective optimization problems. This paper provides an analysis of the influence of the ring, star, lattice, wheel, and tree topologies on the performance of SMPSO (a well-known Pareto-based MOPSO) using many-objective problems. Based on these results, we also propose two MOPSOs that use a combination of topologies: SMPSO-SW and SMPSO-WS. Our experimental results show that SMPSO-SW is able to outperform SMPSO in most of the test problems adopted.

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Notes

  1. 1.

    Although many-objective problems are those having more than 3 objectives, our experiments include test problems with 3 objectives to allow a more clear visualization of the effect of dimensionality increase in objective function space.

  2. 2.

    Without loss of generality, we will assume only minimization problems.

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Acknowledgements

The first author acknowledges support from CONACyT and CINVESTAV-IPN to pursue graduate studies in Computer Science. The second author acknowledges support from CONACyT grant no. 1920 and from a SEP-Cinvestav grant (application no. 4).

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Authors and Affiliations

  1. CINVESTAV-IPN (Evolutionary Computation Group), Avenue IPN 2508, 07360, San Pedro Zacatenco, Ciudad de México, Mexico

    Diana Cristina Valencia-Rodríguez & Carlos A. Coello Coello

Authors
  1. Diana Cristina Valencia-Rodríguez
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  2. Carlos A. Coello Coello
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Corresponding author

Correspondence to Diana Cristina Valencia-Rodríguez .

Editor information

Editors and Affiliations

  1. Southern University of Science and Technology, Shenzhen, China

    Hisao Ishibuchi

  2. City University of Hong Kong, Kowloon Tong, China

    Qingfu Zhang

  3. Southern University of Science and Technology, Shenzhen, China

    Ran Cheng

  4. University of Exeter, Exeter, UK

    Ke Li

  5. Xi'an Jiaotong University, Xi'an, China

    Hui Li

  6. Xidian University, Xi'an, China

    Handing Wang

  7. East China Normal University, Shanghai, China

    Aimin Zhou

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Valencia-Rodríguez, D.C., Coello Coello, C.A. (2021). The Influence of Swarm Topologies in Many-Objective Optimization Problems. In: Ishibuchi, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2021. Lecture Notes in Computer Science(), vol 12654. Springer, Cham. https://doi.org/10.1007/978-3-030-72062-9_31

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  • DOI: https://doi.org/10.1007/978-3-030-72062-9_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72061-2

  • Online ISBN: 978-3-030-72062-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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