Open Access
Issue
RAIRO-Oper. Res.
Volume 58, Number 2, March-April 2024
Page(s) 1473 - 1497
DOI https://doi.org/10.1051/ro/2024013
Published online 05 April 2024
  • S. Abbasi, S. Zahmatkesh, A. Bokhari and M. Hajiaghaei-Keshteli, Designing a vaccine supply chain network considering environmental aspects. J. Cleaner Prod. 417 (2023) 137935. [CrossRef] [Google Scholar]
  • A. Ahmadi-Javid, Entropic value-at-risk: a new coherent risk measure. J. Optim. Theory App. 155 (2012) 1105–1123. [CrossRef] [Google Scholar]
  • M. Alizadeh, A. Makui and M.M. Paydar, Forward and reverse supply chain network design for consumer medical supplies considering biological risk. Comput. Ind. Eng. 140 (2020) 106229. [CrossRef] [Google Scholar]
  • M. Alizadeh, M.S. Pishvaee, H. Jahani, M.M. Paydar and A. Makui, Viable healthcare supply chain network design for a pandemic. Ann. Oper. Res. 328 (2023) 35–73. [CrossRef] [MathSciNet] [Google Scholar]
  • A. Aydemir-Karadag, Bi-objective adaptive large neighborhood search algorithm for the healthcare waste periodic location inventory routing problem. Arabian J. Sci. Eng. 47 (2022) 3861–3876. [CrossRef] [PubMed] [Google Scholar]
  • E. Balci, S. Balci and A. Sofuoglu, Multi-purpose reverse logistics network design for medical waste management in a megacity: Istanbul, Turkey. Environ. Syst. Decis. 42 (2022) 372–387. [CrossRef] [PubMed] [Google Scholar]
  • E.A. Bani, A. Fallahi, M. Varmazyar and M. Fathi, Designing a sustainable reverse supply chain network for COVID-19 vaccine waste under uncertainty. Comput. Ind. Eng. 174 (2022) 108808. [CrossRef] [Google Scholar]
  • Z. Cobandag Guloglu and G.W. Weber, Risk modeling in optimization problems via value at risk, conditional value at risk, and its robustification, in Paper presented at the Modeling, Dynamics, Optimization and Bioeconomics II: DGS III, Porto, Portugal, February 2014, and Bioeconomy VII, Berkeley, USA, March 2014-Selected Contributions 3. Springer International Publishing (2017) 133–145. [Google Scholar]
  • T.N. Cuong, H.-S. Kim and S.-S. You, Decision support system for managing multi-echelon supply chain networks against disruptions using adaptive fractional order control algorithm. RAIRO: Oper. Res. 57 (2023) 787–815. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • F. Glover, Improved linear integer programming formulations of nonlinear integer problems. Manage. Sci. 22 (1975) 455–460. [CrossRef] [Google Scholar]
  • A. Goli, Integration of blockchain-enabled closed-loop supply chain and robust product portfolio design. Comput. Ind. Eng. 179 (2023) 109211. [CrossRef] [Google Scholar]
  • A. Goli and T. Keshavarz, Just-in-time scheduling in identical parallel machine sequence-dependent group scheduling problem. J. Ind. Manage. Optim. 18 (2022) 3807. [CrossRef] [Google Scholar]
  • A. Goli and E.B. Tirkolaee, Designing a portfolio-based closed-loop supply chain network for dairy products with a financial approach: accelerated Benders decomposition algorithm. Comput. Oper. Res. 155 (2023) 106244. [CrossRef] [Google Scholar]
  • A. Goli, A.-M. Golmohammadi and J.-L. Verdegay, Two-echelon electric vehicle routing problem with a developed moth-flame meta-heuristic algorithm. Oper. Manage. Res. 15 (2022) 891–912. [CrossRef] [Google Scholar]
  • A. Goli, A. Ala and M. Hajiaghaei-Keshteli, Efficient multi-objective meta-heuristic algorithms for energy-aware non-permutation flow-shop scheduling problem. Expert Syst. Appl. 213 (2023) 119077. [CrossRef] [Google Scholar]
  • A. Goli, A. Ala and S. Mirjalili, A robust possibilistic programming framework for designing an organ transplant supply chain under uncertainty. Ann. Oper. Res. 328 (2023) 493–530. [CrossRef] [MathSciNet] [Google Scholar]
  • I.A. Gondal and M.H. Sahir, Model for biomass-based renewable hydrogen supply chain. Int. J. Energy Res. 37 (2013) 1151–1159. [CrossRef] [Google Scholar]
  • Ö.F. Görçün, A. Aytekin, S. Korucuk and E.B. Tirkolaee, Evaluating and selecting sustainable logistics service providers for medical waste disposal treatment in the healthcare industry. J. Cleaner Prod. 408 (2023) 137194. [CrossRef] [Google Scholar]
  • K. Govindan, S. Nosrati-Abarghooee, M.M. Nasiri and F. Jolai, Green reverse logistics network design for medical waste management: a circular economy transition through case approach. J. Environ. Manage. 322 (2022) 115888. [CrossRef] [Google Scholar]
  • H. Hazrati, A. Barzegarinegad and H. Siaby-Serajehlo, A hybrid mathematical and decision-making model to determine the amount of economic order considering the discount. Math. Prob. Eng. 2021 (2021) 1–10. [CrossRef] [Google Scholar]
  • Z. Homayouni and M.S. Pishvaee, A bi-objective robust optimization model for hazardous hospital waste collection and disposal network design problem. J. Mater. Cycles Waste Manage. 22 (2020) 1965–1984. [CrossRef] [Google Scholar]
  • S.M.H. Hosseini, F. Behroozi and S.S. Sana, Multi-objective optimization model for blood supply chain network design considering cost of shortage and substitution in disaster. RAIRO: Oper. Res. 57 (2023) 59–85. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • D. Ivanov, Viable supply chain model: integrating agility, resilience and sustainability perspectives – lessons from and thinking beyond the COVID-19 pandemic. Ann. Oper. Res. 319 (2022) 1411–1431. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  • G. Kara, Robust Conditional Value–at–Risk Under Parallelpipe Uncertainty: An Application to Portfolio Optimization. Middle East Technical University (2016). [Google Scholar]
  • S. Kargar, M.M. Paydar and A.S. Safaei, A reverse supply chain for medical waste: a case study in Babol healthcare sector. Waste Manage. 113 (2020) 197–209. [CrossRef] [Google Scholar]
  • S. Kargar, M. Pourmehdi and M.M. Paydar, Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19). Sci. Total Environ. 746 (2020) 141183. [CrossRef] [Google Scholar]
  • R. Lotfi, Y.Z. Mehrjerdi, M.S. Pishvaee, A. Sadeghieh and G.-W. Weber, A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk. Numer. Algebra Control Optim. 11 (2021) 221. [Google Scholar]
  • R. Lotfi, B. Kargar, A. Gharehbaghi and G.-W. Weber, Viable medical waste chain network design by considering risk and robustness. Environ. Sci. Pollut. Res. 29 (2022) 79702–79717. [CrossRef] [PubMed] [Google Scholar]
  • R. Lotfi, B. Kargar, A. Gharehbaghi, H. Hazrati, S. Nazari and M. Amra, Resource-constrained time–cost-quality-energy-environment tradeoff problem by considering blockchain technology, risk and robustness: a case study of healthcare project. Environ. Sci. Pollut. Res. 29 (2022) 63560–63576. [CrossRef] [PubMed] [Google Scholar]
  • R. Lotfi, B. Kargar, M. Rajabzadeh, F. Hesabi and E. Özceylan, Hybrid fuzzy and data-driven robust optimization for resilience and sustainable health care supply chain with vendor-managed inventory approach. Int. J. Fuzzy Syst. 24 (2022) 1216–1231. [CrossRef] [MathSciNet] [Google Scholar]
  • R. Lotfi, H. Hazrati, S.S. Ali, S.M. Sharifmousavi, A. Khanbaba and M. Amra, Antifragile, sustainable and agile healthcare waste chain network design by considering blockchain, resiliency, robustness and risk. Cent. Eur. J. Oper. Res. (2023) 1–34. DOI: 10.1007/s10100-023-00874-0. [Google Scholar]
  • R. Lotfi, R. Hazrati, S. Aghakhani, M. Afshar, M. Amra and S.S. Ali, A data-driven robust optimization in viable supply chain network design by considering Open Innovation and Blockchain Technology. J. Cleaner Prod. (2023) 140369. [Google Scholar]
  • R. Lotfi, M.S. Mehrjardi, P.M. Ansari, F. Zolfaqari and M. Afshar, Antifragile, sustainable, and agile supply chain network design by considering resiliency, robustness, risk, and environmental requirements. Environ. Sci. Pollut. Res. 30 (2023) 106442–106459. [CrossRef] [Google Scholar]
  • R. Lotfi, P. MohajerAnsari, M.M.S. Nevisi, M. Afshar, S.M.R. Davoodi and S.S. Ali, A viable supply chain by considering vendor-managed-inventory with a consignment stock policy and learning approach. Results Eng. 21 (2024) 101609. [CrossRef] [Google Scholar]
  • X. Mei, H. Hao, Y. Sun, X. Wang and Y. Zhou, Optimization of medical waste recycling network considering disposal capacity bottlenecks under a novel coronavirus pneumonia outbreak. Environ. Sci. Pollut. Res. 29 (2022) 79669–79687. [CrossRef] [PubMed] [Google Scholar]
  • B. Mosallanezhad, F. Gholian-Jouybari, L.E. Cárdenas-Barrón and M. Hajiaghaei-Keshteli, The IoT-enabled sustainable reverse supply chain for COVID-19 Pandemic Wastes (CPW). Eng. App. Artif. Intell. 120 (2023) 105903. [CrossRef] [Google Scholar]
  • R. Negarandeh and A. Tajdin, A robust fuzzy multi-objective programming model to design a sustainable hospital waste management network considering resiliency and uncertainty: a case study. Waste Manage. Res. 40 (2022) 439–457. [CrossRef] [PubMed] [Google Scholar]
  • P. Nejat, F. Jomehzadeh, M.M. Taheri, M. Gohari and M.Z.A. Majid, A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renew. Sustain. Energy Rev. 43 (2015) 843–862. [CrossRef] [Google Scholar]
  • A. Paeizi, A. Makui and M.S. Pishvaee, A multi-stage stochastic programming approach for an inventory–routing problem considering life cycle. RAIRO: Oper. Res. 57 (2023) 2537–2559. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • E. Shadkam, Cuckoo optimization algorithm in reverse logistics: a network design for COVID-19 waste management. Waste Manage. Res. 40 (2022) 458–469. [CrossRef] [PubMed] [Google Scholar]
  • H.D. Sherali and W.P. Adams, A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems. Vol. 31. Springer Science & Business Media (2013). [Google Scholar]
  • S. Suksee and S. Sindhuchao, GRASP with ALNS for solving the location routing problem of infectious waste collection in the Northeast of Thailand. Int. J. Ind. Eng. Comput. 12 (2021) 305–320. [Google Scholar]
  • E.B. Tirkolaee and N.S. Aydın, A sustainable medical waste collection and transportation model for pandemics. Waste Manage. Res. 39 (2021) 34–44. [CrossRef] [PubMed] [Google Scholar]
  • E.B. Tirkolaee, P. Abbasian and G.-W. Weber, Sustainable fuzzy multi-trip location-routing problem for medical waste management during the COVID-19 outbreak. Sci. Total Environ. 756 (2021) 143607. [CrossRef] [Google Scholar]
  • E.B. Tirkolaee, A. Goli and S. Mirjalili, Circular economy application in designing sustainable medical waste management systems. Environ. Sci. Pollut. Res. 29 (2022) 79667–79668. [CrossRef] [PubMed] [Google Scholar]
  • A.E. Torkayesh, H.R. Vandchali and E.B. Tirkolaee, Multi-objective optimization for healthcare waste management network design with sustainability perspective. Sustainability 13 (2021) 8279. [CrossRef] [Google Scholar]
  • H. Yu, X. Sun, W.D. Solvang and X. Zhao, Reverse logistics network design for effective management of medical waste in epidemic outbreaks: insights from the coronavirus disease 2019 (COVID-19) outbreak in Wuhan (China). Int. J. Environ. Res. Publ. Health 17 (2020) 1770. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.