IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2018i1p18-d192076.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/1/18/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/1/18/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shi, Xing & Tian, Zhichao & Chen, Wenqiang & Si, Binghui & Jin, Xing, 2016. "A review on building energy efficient design optimization rom the perspective of architects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 872-884.
    2. Machairas, Vasileios & Tsangrassoulis, Aris & Axarli, Kleo, 2014. "Algorithms for optimization of building design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 101-112.
    3. A.M. Fogheri, 2015. "Energy Efficiency in Public Buildings," Rivista economica del Mezzogiorno, Società editrice il Mulino, issue 3-4, pages 763-784.
    4. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    5. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    6. Yaolin Lin & Shiquan Zhou & Wei Yang & Chun-Qing Li, 2018. "Design Optimization Considering Variable Thermal Mass, Insulation, Absorptance of Solar Radiation, and Glazing Ratio Using a Prediction Model and Genetic Algorithm," Sustainability, MDPI, vol. 10(2), pages 1-15, January.
    7. Yunsong Han & Hong Yu & Cheng Sun, 2017. "Simulation-Based Multiobjective Optimization of Timber-Glass Residential Buildings in Severe Cold Regions," Sustainability, MDPI, vol. 9(12), pages 1-18, December.
    8. Bohong Zheng & Komi Bernard BEDRA & Jian Zheng & Guoguang Wang, 2018. "Combination of Tree Configuration with Street Configuration for Thermal Comfort Optimization under Extreme Summer Conditions in the Urban Center of Shantou City, China," Sustainability, MDPI, vol. 10(11), pages 1-23, November.
    9. Si, Binghui & Tian, Zhichao & Jin, Xing & Zhou, Xin & Tang, Peng & Shi, Xing, 2016. "Performance indices and evaluation of algorithms in building energy efficient design optimization," Energy, Elsevier, vol. 114(C), pages 100-112.
    10. Kailun Feng & Weizhuo Lu & Shiwei Chen & Yaowu Wang, 2018. "An Integrated Environment–Cost–Time Optimisation Method for Construction Contractors Considering Global Warming," Sustainability, MDPI, vol. 10(11), pages 1-23, November.
    11. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdo Abdullah Ahmed Gassar & Choongwan Koo & Tae Wan Kim & Seung Hyun Cha, 2021. "Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review," Sustainability, MDPI, vol. 13(17), pages 1-47, September.
    2. Si, Binghui & Tian, Zhichao & Jin, Xing & Zhou, Xin & Tang, Peng & Shi, Xing, 2016. "Performance indices and evaluation of algorithms in building energy efficient design optimization," Energy, Elsevier, vol. 114(C), pages 100-112.
    3. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    4. Nayara R. M. Sakiyama & Joyce C. Carlo & Leonardo Mazzaferro & Harald Garrecht, 2021. "Building Optimization through a Parametric Design Platform: Using Sensitivity Analysis to Improve a Radial-Based Algorithm Performance," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    5. Eleftheria Touloupaki & Theodoros Theodosiou, 2017. "Performance Simulation Integrated in Parametric 3D Modeling as a Method for Early Stage Design Optimization—A Review," Energies, MDPI, vol. 10(5), pages 1-18, May.
    6. Shaoxiong Li & Le Liu & Changhai Peng, 2020. "A Review of Performance-Oriented Architectural Design and Optimization in the Context of Sustainability: Dividends and Challenges," Sustainability, MDPI, vol. 12(4), pages 1-36, February.
    7. Østergård, Torben & Jensen, Rasmus L. & Maagaard, Steffen E., 2016. "Building simulations supporting decision making in early design – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 187-201.
    8. Si, Binghui & Tian, Zhichao & Jin, Xing & Zhou, Xin & Shi, Xing, 2019. "Ineffectiveness of optimization algorithms in building energy optimization and possible causes," Renewable Energy, Elsevier, vol. 134(C), pages 1295-1306.
    9. Mostavi, Ehsan & Asadi, Somayeh & Boussaa, Djamel, 2017. "Development of a new methodology to optimize building life cycle cost, environmental impacts, and occupant satisfaction," Energy, Elsevier, vol. 121(C), pages 606-615.
    10. Guariso, Giorgio & Sangiorgio, Matteo, 2019. "Multi-objective planning of building stock renovation," Energy Policy, Elsevier, vol. 130(C), pages 101-110.
    11. Østergård, Torben & Jensen, Rasmus Lund & Maagaard, Steffen Enersen, 2018. "A comparison of six metamodeling techniques applied to building performance simulations," Applied Energy, Elsevier, vol. 211(C), pages 89-103.
    12. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    13. Chen, Xia & Geyer, Philipp, 2022. "Machine assistance in energy-efficient building design: A predictive framework toward dynamic interaction with human decision-making under uncertainty," Applied Energy, Elsevier, vol. 307(C).
    14. Li, Hong Xian & Li, Yan & Jiang, Boya & Zhang, Limao & Wu, Xianguo & Lin, Jingyi, 2020. "Energy performance optimisation of building envelope retrofit through integrated orthogonal arrays with data envelopment analysis," Renewable Energy, Elsevier, vol. 149(C), pages 1414-1423.
    15. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "Impact of adjustment strategies on building design process in different climates oriented by multiple performance," Applied Energy, Elsevier, vol. 266(C).
    16. Ramos Ruiz, Germán & Fernández Bandera, Carlos & Gómez-Acebo Temes, Tomás & Sánchez-Ostiz Gutierrez, Ana, 2016. "Genetic algorithm for building envelope calibration," Applied Energy, Elsevier, vol. 168(C), pages 691-705.
    17. Yue, Naihua & Caini, Mauro & Li, Lingling & Zhao, Yang & Li, Yu, 2023. "A comparison of six metamodeling techniques applied to multi building performance vectors prediction on gymnasiums under multiple climate conditions," Applied Energy, Elsevier, vol. 332(C).
    18. Shi, Xing & Tian, Zhichao & Chen, Wenqiang & Si, Binghui & Jin, Xing, 2016. "A review on building energy efficient design optimization rom the perspective of architects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 872-884.
    19. Aste, Niccolò & Leonforte, Fabrizio & Manfren, Massimiliano & Mazzon, Manlio, 2015. "Thermal inertia and energy efficiency – Parametric simulation assessment on a calibrated case study," Applied Energy, Elsevier, vol. 145(C), pages 111-123.
    20. de Almeida Rocha, Ana Paula & Reynoso-Meza, Gilberto & Oliveira, Ricardo C.L.F. & Mendes, Nathan, 2020. "A pixel counting based method for designing shading devices in buildings considering energy efficiency, daylight use and fading protection," Applied Energy, Elsevier, vol. 262(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:18-:d:192076. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.