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Optimization of Indoor Luminaire Layout for General Lighting Scheme Using Improved Particle Swarm Optimization

Author

Listed:
  • Ji-Qing Qu

    (College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210000, China)

  • Qi-Lin Xu

    (College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210000, China)

  • Ke-Xue Sun

    (College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210000, China
    Nation-Local Joint Project Engineering Lab of RF Integration & Micropackage, Nanjing University of Posts and Telecommunications, Nanjing 210000, China)

Abstract

An improved mathematical model and an improved particle swarm optimization (IPSO) are proposed for the complex design parameters and conflicting design goals of the indoor luminaire layout (ILL) problem. The ILL problem is formulated as a nonlinear constrained mixed-variable optimization problem that has four decision variables. For a general lighting scheme (GLS), the number and location of luminaires can be uniquely determined by optimizing four decision variables, which avoid using program loops to determine the number of luminaires. We improve the particle swarm optimization (PSO) in three aspects: (1) up-down probabilistic rounding (UDPR) method proposed to solve mixed integer, (2) improving the velocity of the best global particle, and (3) using nonlinear inertia weights with random items. The IPSO has better optimization results in an office study compared with the PSO and genetic algorithm (GA). The results are validated by DIALux simulation software, and a maximum deviation of 2.2% is found. The validated results show that the method using four decision variables increased the speed by 10.6% and the success rate by 23.33%. Furthermore, Indoor Luminaire Layout System APP is designed to provide guidelines visually for lighting designers and related researchers.

Suggested Citation

  • Ji-Qing Qu & Qi-Lin Xu & Ke-Xue Sun, 2022. "Optimization of Indoor Luminaire Layout for General Lighting Scheme Using Improved Particle Swarm Optimization," Energies, MDPI, vol. 15(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1482-:d:751554
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    References listed on IDEAS

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    1. Jing Li & Chi-Hui Wu & Chien-Wen Chen & Yi-Fen Huang & Ching-Torng Lin, 2020. "Apply Fuzzy DEMATEL to Explore the Decisive Factors of the Auto Lighting Aftermarket Industry in Taiwan," Mathematics, MDPI, vol. 8(7), pages 1-27, July.
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    Cited by:

    1. Yukun Dong & Yu Zhang & Fubin Liu & Zhengjun Zhu, 2022. "Research on an Optimization Method for Injection-Production Parameters Based on an Improved Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 15(8), pages 1-18, April.

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