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Performance Assessment of Algorithms for Building Energy Optimization Problems with Different Properties

Author

Listed:
  • Binghui Si

    (School of Architecture, Southeast University, Nanjing 210096, China)

  • Zhichao Tian

    (School of Architecture, Southeast University, Nanjing 210096, China)

  • Wenqiang Chen

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China)

  • Xing Jin

    (School of Architecture, Southeast University, Nanjing 210096, China)

  • Xin Zhou

    (School of Architecture, Southeast University, Nanjing 210096, China)

  • Xing Shi

    (School of Architecture, Southeast University, Nanjing 210096, China)

Abstract

Assessing the performance of algorithms in solving building energy optimization (BEO) problems with different properties is essential for selecting appropriate algorithms to achieve the best design solution. This study begins with a classification of the properties of BEO problems from three perspectives, namely, design variables, objective functions, and constraints. An analytical approach and a numerical approach are proposed to determine the properties of BEO problems. Six BEO test problems with different properties, namely, continuous vs. discrete, convex vs. non-convex, linear vs. non-linear, uni-modal vs. multimodal, and single-dimensional vs. multi-dimensional, are composed to evaluate the performance of algorithms. The selected optimization algorithms for performance assessment include the discrete Armijo gradient, Particle Swarm Optimization (PSO), Hooke-Jeeves, and hybrid PSO and Hooke-Jeeves. The assessment results indicate that multimodality can cause Hooke-Jeeves and discrete Armijo gradient algorithms to fall into local optima traps. The convex, non-convex, linear and non-linear properties of uni-modal BEO problems have little impact on the performance behavior of the algorithms. The discrete Armijo gradient and Hooke-Jeeves are not recommended for solving discrete and multi-dimensional BEO problems.

Suggested Citation

  • Binghui Si & Zhichao Tian & Wenqiang Chen & Xing Jin & Xin Zhou & Xing Shi, 2018. "Performance Assessment of Algorithms for Building Energy Optimization Problems with Different Properties," Sustainability, MDPI, vol. 11(1), pages 1-22, December.
  • Handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:18-:d:192076
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    References listed on IDEAS

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    Cited by:

    1. Ru Ji & Shilin Qu, 2019. "Investigation and Evaluation of Energy Consumption Performance for Hospital Buildings in China," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
    2. Hou, Dan & Huang, Jiayu & Wang, Yanyu, 2023. "A comparison of approaches with different constraint handling techniques for energy-efficient building form optimization," Energy, Elsevier, vol. 277(C).
    3. Hyeongjin Moon & Jae-Young Jeon & Yujin Nam, 2020. "Development of Optimal Design Method for Ground-Source Heat-Pump System Using Particle Swarm Optimization," Energies, MDPI, vol. 13(18), pages 1-17, September.
    4. Hyeongjin Moon & Hongkyo Kim & Yujin Nam, 2019. "Study on the Optimum Design of a Ground Heat Pump System Using Optimization Algorithms," Energies, MDPI, vol. 12(21), pages 1-17, October.

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