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All issues Volume 55 / No 2 (March-April 2021) RAIRO-Oper. Res., 55 2 (2021) 997-1013 References
Free Access
Issue
RAIRO-Oper. Res.
Volume 55, Number 2, March-April 2021
Page(s) 997 - 1013
DOI https://doi.org/10.1051/ro/2021048
Published online 07 May 2021
  • I. Abadi, M. Mohammadnejad, R. Sadeghian and F. Ahmadizar, A new mathematical model for closed-loop supply chains considering product pricing, fleet of heterogeneous vehicles, and inventory costs. J. Optim. Ind. Eng. 10 (2017) 29–40. [Google Scholar]
  • A. Abedi and W. Zhu, An optimisation model for purchase, production and distribution in fish supply chain – a case study. Int. J. Prod. Res. 55 (2017) 3451–3464. [Google Scholar]
  • A. Barbosa-Póvoa, As cadeias de abastecimento e a sustentabilidade (Supply chains and sustainability). Boletim APDIO 55 (2016) 5–9. [Google Scholar]
  • G. Brock, V. Pihur, S. Datta and S. Datta, clValid: An R package for cluster validation. J. Stat. Softw. 25 (2008) 1–22. [Google Scholar]
  • R. Byrd, J. Nocedal and R. Waltz, KNITRO: An integrated package for nonlinear optimization. In: Large-scale Nonlinear Optimization. Springer (2006) 35–59. [Google Scholar]
  • A. Carr and L. Smeltzer, The relationship of strategic purchasing to supply chain management. Eur. J. Purchasing Supply Manage. 5 (1999) 43–51. [Google Scholar]
  • T. Choi, K. Govindan, X. Li and Y. Li, Innovative supply chain optimization models with multiple uncertainty factors. Ann. Oper. Res. 257 (2017) 1–14. [Google Scholar]
  • M. Christopher, Logistics & Supply Chain Management. Pearson, UK (2016). [Google Scholar]
  • M. Correia and A. Carvalho, Cadeias de abastecimento de produtos congelados (Supply chains of frozen products). Boletim APDIO 55 (2016) 18–21. [Google Scholar]
  • J. Czyzyk, M. Mesnier and J. Moré, The NEOS server. IEEE J. Comput. Sci. Eng. 5 (1998) 68–75. [Google Scholar]
  • A. Derakhshan, S. Hosseini and A. Hassani, Modeling a multi-period multi-product closed-loop supply chain network design problem considering reused cost and capacity constraints. Int. J. Supply Oper. Manage. 4 (2017) 133–149. [Google Scholar]
  • A. Diogo, Um modelo de reutilização de caixas do fornecedor: caso de estudo (A model for reusing supplier boxes). Master Thesis. Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (2015). [Google Scholar]
  • E. Dolan, The NEOS Server 4.0 administrative guide. Technical Memorandum ANL/MCS-TM-250. Mathematics and Computer Science Division, Argonne National Laboratory (2001). [Google Scholar]
  • D. Fernández, C. Pozo, R. Folgado, G. Guillén-Gosálbez and L. Jiménez, Multiperiod model for the optimal production planning in the industrial gases sector. Appl. Energy 206 (2017) 667–682. [Google Scholar]
  • B. Fleischmann and H. Meyr, Planning hierarchy, modeling and advanced planning systems. Handbooks Oper. Res. Manage. Sci. 11 (2003) 455–523. [Google Scholar]
  • B. Fleischmann, H. Meyr and M. Wagner, Advanced planning. In: Supply Chain Management and Advanced Planning, Springer (2008) 81–106. [Google Scholar]
  • S. Gold, S. Seuring and P. Beske, Sustainable supply chain management and inter-organizational resources: a literature review. Corporate Soc. Responsibility Environ. Manage. 17 (2010) 230–245. [Google Scholar]
  • K. Govindan, H. Soleimani and D. Kannan, Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future. Eur. J. Oper. Res. 240 (2015) 603–626. [Google Scholar]
  • W. Gropp and J. Moré, Optimization environments and the NEOS Server, edited by M.Buhman Server and A. Iserles. In: Approximation Theory and Optimization. Cambridge University Press (1997) 167–182. [Google Scholar]
  • H. Hou, S. Chaudhry, Y. Chen and M. Hu, Physical distribution, logistics, supply chain management, and the material flow theory: a historical perspective. Inf. Technol. Manage. 18 (2017) 107–117. [Google Scholar]
  • A. Hübner, H. Kuhn and M. Sternbeck, Demand and supply chain planning in grocery retail: an operations planning framework. Int. J. Retail Distrib. Manage. 41 (2013) 512–530. [Google Scholar]
  • L. Kaufman and P. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley & Sons (2009). [Google Scholar]
  • B. Kernighan, R. Fourer and D. Gay, AMPL: A Modeling Language for Mathematical Programming. Scientific Press, San Francisco (1993). [Google Scholar]
  • D. Ketchen and G. Hult, Bridging organization theory and supply chain management: the case of best value supply chains. J. Oper. Manage. 25 (2007) 573–580. [Google Scholar]
  • P. Kouvelis and M. Rosenblatt, A mathematical programming model for global supply chain management: conceptual approach and managerial insights. In: Supply Chain Management: Models, Applications, and Research Directions (2002) 245–277. [Google Scholar]
  • Z. Liu and A. Nagurney, Multiperiod competitive supply chain networks with inventorying and a transportation network equilibrium reformulation. Optim. Eng. 13 (2012) 471–503. [Google Scholar]
  • S. Mansouri, D. Gallear and M. Askariazad, Decision support for build-to-order supply chain management through multiobjective optimization. Int. J. Prod. Econ. 135 (2012) 24–36. [Google Scholar]
  • G. Mehmeti, A literature review on supply chain management evolution. In: Economic and Social Development: Book of Proceedings (2016) 482. [Google Scholar]
  • M. Melo, S. Nickel and F. Saldanha-Da-Gama, Facility location and supply chain management – a review. Eur. J. Oper. Res. 196 (2009) 401–412. [Google Scholar]
  • M. Moreno and J. Montagna, A multiperiod model for production planning and design in a multiproduct batch environment. Math. Comput. Model. 49 (2009) 1372–1385. [Google Scholar]
  • S. Neiro and J. Pinto, A general modeling framework for the operational planning of petroleum supply chains. Comput. Chem. Eng. 28 (2004) 871–896. [Google Scholar]
  • J. Orlin and E. Nasrabadi, 15.053 Optimization methods in management science. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA (2018). [Google Scholar]
  • A. Ortíz-Gómez, V. Rico-Ramirez and S. Hernandez-Castro, Mixed-integer multiperiod model for the planning of oilfield production. Comput. Chem. Eng. 26 (2002) 703–714. [Google Scholar]
  • G. Perakis and M. Zaretsky, Multiperiod models with capacities in competitive supply chain. Prod. Oper. Manage. 17 (2008) 439–454. [Google Scholar]
  • R Core Team, R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria https://www.R-project.org/ (2016). [Google Scholar]
  • A. Rajeev, R. Pati, S. Padhi and K. Govindan, Evolution of sustainability in supply chain management: a literature review. J. Cleaner Prod. 162 (2017) 299–314. [Google Scholar]
  • E. Schulz, S. Diaz and A. Bandoni, Supply chain optimisation in a petrochemical complex. Comput. Aided Chem. Eng. 18 (2004) 997–1002. [Google Scholar]
  • S. Seuring, A review of modeling approaches for sustainable supply chain management. Decis. Support Syst. 54 (2013) 1513–1520. [Google Scholar]
  • D. Simchi-Levi, P. Kaminsky and E. Simchi-Levi, Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies, 4th edition. McGraw-Hill Education (2019). [Google Scholar]
  • H. Stadtler, Supply chain management and advanced planning – basics, overview and challenges. Eur. J. Oper. Res. 163 (2005) 575–588. [Google Scholar]
  • J. Stock and S. Boyer, Developing a consensus definition of supply chain management: a qualitative study. Int. J. Phys. Distrib. Logistics Manage. 39 (2009) 690–711. [Google Scholar]
  • A. Teixeira, E. Cost e Silva, C. Lopes and J. Santos, Supply chain purchasing domain optimization in a portuguese retail company. Springer Proc. Math. Stat. 278 (2019) 199–214. [Google Scholar]
  • J. Wang and Y. Shu, Fuzzy decision modeling for supply chain management. Fuzzy Sets and Systems 150 (2005) 107–127. [Google Scholar]
  • Y. Zhao, R and Data Mining: Examples and Case Studies. Academic Press (2012). [Google Scholar]

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