An optimization model to support long-term maintenance of multifamily residential buildings

openaccess, Vol. 604 (12) 2022 / wtorek, 27 grudnia, 2022

(Open Access)

DOI: 10.15199/33.2022.12.12

Bucoń Robert, Czarnigowska Agata. 2022. An optimization model to support long-term maintenance of multifamily residential buildings. Volume 604. Issue 12. Pages 46-49. Article in PDF file

Accepted for publication: 20.10.200 r.

The article presents amodel to support decisions related to long-term planning of housing maintenance. A method of quantifying the building condition and an optimization algorithm were proposed, maximizing the benefits of repair and modernization activities (expressed by the increment of the building condition assessment)with the assumption ofminimizing the cost of these activities. The model takes into account practical constraints related to budget assumptions, sequence of works and deadlines, supporting the allocation of activities in the planned time horizon. The developedmethodologywas implemented in the formof a computer systemand can be regarded as a usefultool for supporting the decision-making process at the maintenance stage of multifamily residential buildings.
  1. Jensen PA, Maslesa E, Berg JB, Thuesen C. 10 questions concerning sustainable building renovation. Build Environ. 2018; https://doi. org/10.1016/j.buildenv. 2018.06.051.
  2. Sharif SA, Hammad A. Simulation-Based Multi-Objective Optimization of institutional building renovation considering energy consumption. Life- Cycle Cost and Life-Cycle Assessment. J. Build. Eng. 2021; https://doi. org/10.1016/j. jobe. 2018.11.006.
  3. Bansal S, Biswas S, Singh SK. Holistic assessment of existing buildings: Indian context. J.Build. Eng. 2019; 2019.100793.
  4. Nowogońska B.AMethodology for Determining the Rehabilitation Needs of Buildings. Appl. Sci. 2021; https://doi. org/10.3390/app10113873.
  5.  CarbonariA, CorneliA, Di Giuda GM, Ridolfi L, Villa V. Decision support systemformulti-criteria assessment of large building stocks J. Civ. Eng. Manag. 2019; https://doi. org/10.3846/jcem. 2019.9872.
  6. Serrano-JimenezA, Femenias P, Thuvander L, Barrios-PaduraA.Amulti- criteria decision support method towards selecting feasible and sustainable housing renovation strategies. J. Clean. Prod. 2021; https://doi. org/10.1016/j. jclepro. 2020.123588.
  7.  Bucoń R, Czarnigowska A. A model to support long-term building maintenance planning for multifamily housing. J. Build. Eng. 2021; https://doi. org/10.1016/j. jobe. 2021.103000.
  8. Son H, Kim C. Evolutionary Many-Objective Optimization for Retrofit Planning in Public Buildings: A Comparative Study. J. Clean. Prod. 2018; https://doi. org/10.1016/j. jclepro. 2018.04.102.
  9. Mejjaouli S, Alzahrani M. Decision-making model for optimum energy retrofitting strategies in residential buildings. Sustain. Prod. Consum. 2020; 2020.07.008.
  10. Galimshina A, Moustapha M, Hollberg A, Padey P, Lasvaux S, Sudret B, Habert G. Statistical method to identify robust building renovation choices for environmental and economic performance. Build Environ. 2020; https://doi. org/10.1016/j. buildenv. 2020.107143.
  11. Cho K, Kim T. Optimized scheduling method for office building renovation projects. Expert Syst. Appl. 2021; eswa. 2020.114212.
  12. Cho K, Yoon Y. Decision Support Model for Determining Cost-Effective Renovation Time. J.Manag. Eng. 2016; https://doi. org/10.1061/(ASCE) ME. 1943-5479.0000418
  13. HauashdhA, Jailani J, Rahman IA,AL-fadhali N. Strategic approaches towards achieving sustainable and effective building maintenance practices in maintenance-managed buildings:Acombination of expert interviews and a literature review. J. Build. Eng. 2022; https://doi. org/10.1016/j. jobe. 2021.103490
  14. Hauashdha A, Jailani J, Rahman IA, AL-fadhal N. Structural equation model for assessing factors affecting building maintenance success. J. Build. Eng. 2021; https://doi. org/10.1016/j. jobe. 2021.102680
  15.  Kamari A, Corrao R, Kirkegaard PH. Sustainability focused decision- -making in building renovation. Int. J. Sustain. Built Environ. 2017; https://doi. org/10.1016/j.ijsbe. 2017.05.001
dr inż. Robert Bucoń, Politechnika Lubelska, Wydział Budownictwa i Architektury ORCID: 0000-0002-9397-639X
dr inż. Agata Czarnigowska, Politechnika Lubelska, Wydział Budownictwa i Architektury ORCID: 0000-0003-3715-3521

dr inż. Robert Bucoń, Politechnika Lubelska, Wydział Budownictwa i Architektury ORCID: 0000-0002-9397-639X

Full paper:

DOI: 10.15199/33.2022.12.12

Article in PDF file