Optimal model for selection of material with low emission of indoor air pollutants

Seong-Min Kwon, Byung-Soo Kim

Article ID: 2545
Vol 8, Issue 1, 2024

VIEWS - 242 (Abstract) 124 (PDF)

Abstract


When the amount of data to be reviewed is large and the properties of the material are complex, it is difficult to make a rational decision in selecting the optimal material. Therefore, in this study, we tried to develop an optimization model that comprehensively considers user requirements, performance and economic feasibility of materials for selecting materials with low emission of indoor air pollutants. To this end, a database was constructed considering the economic feasibility by applying the concept of LCC (Life Cycle Cost) and presenting price range options that can be selected by the user. A genetic algorithm was used to construct a model to derive a material plan that could achieve the target score while satisfying economic feasibility and user requirements. As a result of model verification and verification cases, materials were selected only within the range according to the price range option and user selection criteria for each space and part. The efficiency and effectiveness of this model were confirmed. In this study, reliable results can be presented by presenting a model that can automatically select an algorithm for the optimal preferred material selection problem that is difficult for humans to solve cognitively with database construction and user selection information. Since it can be used in other fields, scalability and usability of this model are expected. In addition, it helps user to reduce the time of the material selection process and the price of materials is also considered, so that it is expected to help improve the economic feasibility of overall construction.

Keywords


material selection; user-choice-based; optimal preferred materials; genetic algorithm; economic feasibility

Full Text:

PDF


References


De Jong KA (1975). An Analysis of the Behavior of a Class of Genetic Adaptive Systems [PhD thesis]. University of Michigan.

Hwang S, Tae C, Shin U (2016). A study on the score of issues by certification grade in the G-SEED for office buildings. Journal of the Korean Solar Energy Society 36(5): 9–18. doi: 10.7836/kses.2016.36.5.009

Josefin P, Wang T, Hagberg J (2019). Indoor air quality of newly built low-energy preschools—Are chemical emissions reduced in houses with eco-labelled building materials. Indoor and Built Environment 28(4): 506–519. doi: 10.1177/1420326X18792600

Khatri KA, Shah KB, Logeshwaran J, Shrestha A (2023). Genetic algorithm based techno-economic optimization of an isolated hybrid energy system. CRF. doi: 10.21917/ijme.2023.0249

Kim CN, Kim YK, Kim SS, et al. (2007) The development of estimation program of indoor air pollution concentration (KLAir-E) according to air exchange rate and pollutant emission rate of finishing building materials. Journal of the Architectural Institute of Korea 27(1): 913–916.

Kim DB, Bae JH, Lee BH (2015). A basic study for the development of green construction materials classification structure through comparing with green building certification systems (Korean). Journal of the Architectural Institute of Korea 135–136.

Kim JI (2009). A Selection Support Model for Floor Finishing Materials of Office Building based on Project Similarity and Materials Performance [Master’s thesis]. University of Seoul.

Kim KH, Kim KR, Hwang YG. (2008) Selection method of eco-friendly finishing materials considering cost efficiency for the aged housing remodeling projects. Korean Journal of Construction Engineering and Management 9(4): 84–91.

Kim O, Rhee DJ, Park JC (2005). A study on the classification of finishing materials for the establishment of indoor air pollutants data-base (Korean). Journal of the Architectural Institute of Korea 25(1): 395–398.

Korea Institute of Construction Technology (KICT) (2007). Construction Information Classification. Available online: http://gseed.or.kr/ (accessed on 7 August 2023).

Korea Institute of Construction Technology (KICT) (2018). G-SEED guidebook.

Kwon GD, Lee DH, Lee SH, et al. (2010). A finish material management process for indoor air quality-Focused on apartment buildings. KIEAE Journal 10(6):123–130.

Lee KS (2010). Optimal Design of Nielsen Arch Bridges by Using Genetic Algorithm [PhD thesis]. Chung-Ang University.

Lee SH, Lee JS (2017). An economic evaluation of green business buildings in consideration of life-cycle costs and benefits. Journal of the Architectural Institute of Korea Planning & Design 33(7): 57–65. doi: 10.5659/JAIK_PD.2017.33.7.57

Lee SO (2014). An analysis on cost importance for issues of G-SEED (Korean). Journal of the Architectural Institute of Korea 34(2): 431–432.

Lee SO, Cho DW, Park CY (2014). Development of credit calculation methodologies in G-SEED for multi-residential buildings. Journal of the Architectural Institute of Korea Planning & Design 30(12): 289–297. doi: 10.5659/JAIK_PD.2014.30.12.289

Lim SY (2010). A Study on Improving the Estimation Accuracy of Apartment Project Cost [Master’s thesis]. Chonnam National University.

Mathiyazhagan K, Gnanavelbabu A, Lokesh Prabhuraj B (2019). A sustainable assessment model for material selection in construction industries perspective using hybrid MCDM approaches. Journal of Advances in Management Research 16(2): 234–259. doi: 10.1108/JAMR-09-2018-0085

Park HJ, Kook KJ (2014). Metadata based information management prototype system of building material. Journal of the Architectural Institute of Korea Structure & Construction 30(5): 109–116. doi: 10.5659/JAIK_SC.2014.30.5.109

Sohail A (2023). Genetic Algorithms in the Fields of Artificial Intelligence and Data Sciences. Annals of Data Science 10(4): 1007–1018.

Wang SJ, Tae SH (2018). A study on the automatic assessment of materials and resources in green building certification through integrated green building materials database (Korean). Journal of the Architectural Institute of Korea 38(2): 452–455.




DOI: https://doi.org/10.24294/jipd.v8i1.2545

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Seong-Min Kwon, Byung-Soo Kim

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.