A stochastic Fermatean fuzzy-based multi-choice conic goal programming approach for sustainable supply chain management in end-of-life buildings

Deliktaş D., Karagoz S., Simić V., AYDIN N.

Journal of Cleaner Production, vol.382, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 382
  • Publication Date: 2023
  • Doi Number: 10.1016/j.jclepro.2022.135305
  • Journal Name: Journal of Cleaner Production
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Debris management, End-of-life buildings, Multi-choice conic goal programming, Stochastic optimization, Supply chain network design, Sustainable development
  • Yıldız Technical University Affiliated: Yes


© 2022 Elsevier LtdDue to natural disasters, urban transformations and many other factors, sustainable end-of-life buildings (ELBs) waste management is gaining importance within the last decades, which is vigorous for both economic and conservation matters. Turkey is located on active zones in terms of natural disasters and faced numerous destructive events. Therefore, the government initiated a program to renew the ELBs. Even though several studies analyzed post-disaster debris management, there are not many studies focusing on pre-disaster debris management. Thus, this study proposes a two-stage stochastic model to optimize the supply chain network of ELBs and manage the debris stemmed from the destruction of the ELBs. With this aim, the criteria and the alternatives for evaluating the objectives are defined, experts’ evaluations for objectives are integrated into the model, Fermatean fuzzy-based weighting approach is introduced to transfer the experts’ views on the importance of the objectives, and the stochastic Fermatean fuzzy-based multi-choice conic goal programming (FF-MCCGP) and the revised-MCGP methods are used to provide optimal facility locations, and the amount of debris to transfer within the network. The stochastic FF-MCCGP approach outperforms the revised-MCGP in most cases, where they are compared. Furthermore, a sustainable management strategy is offered to control the economic, pollution, land-use stress and population health factors. This study is one of the pioneer studies that eases the consequences of diseases, urban transformation, wars, and other factors by considering the renewal of ELBs, and method can be upgraded dynamically regarding the potential needs and conditions as it offers a global road map.