Design of Reverse Logistics Networks for Multiproducts, Multistates, and Multiprocessing Alternatives

  • Marc Chouinard
  • Sophie D’Amours
  • Daoud Aït-Kadi
Part of the Springer Series in Advanced Manufacturing book series (SSAM)


This chapter proposes a modeling methodology for designing reverse logistics networks. The model aims at determining the location and missions of sites for the recovery of unused products from ultimate consumers, valorization or clean disposal of recovered products, redistribution of reusable materials, and attribution of new or reusable (valorized) products. Valorization activities refer to repair, refurbishing, reassembling, product disassembly for reusable material recovery (cannibalization), and recycling. The proportion of recovered product volumes to orient to valorization and clean disposal activities is not known a priori but is determined according to demand and return volumes, site capacities, and the general anticipated state of recovered product volumes. This model may be used to evaluate the impact of reintegrating valorized products (finished products and spare parts) into current supply chains initially designed only for distribution and maintenance of new products. The chapter discusses key parameters such as the localization and estimation of potential returns and demands for new and reusable (valorized) products, as well as the probability that a returned product be in a specific state, which could lead to one or many processing alternatives (repair, disassembly, clean disposal, etc.). This mathematical model is inspired by the recent healthcare allocation and valorization of the wheelchair policy of the Province of Quebec (Canada), governed and managed by a governmental agency.


Supply Chain Product Family Processing Alternative Spare Part Reverse Logistics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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8.8 References

  1. Arntzen BC, Brown GG, Harrison TP, Trafton LL, (1995) Global supply chain management at digital equipment corporation. Interfaces, 25(1):69–93.Google Scholar
  2. Ballou RH, (1994) Measuring transport costing error in customer aggregation for facility location. Transportation Journal, 33(3):49–59.Google Scholar
  3. Bloemhof-Ruuward JM, Krikke H, Van Wassenhove LN, (2004) OR models for eco-eco closed-loop supply chain optimization. In: Reverse Logistics: Quantitative Models for Closed-Loop Supply Chain. Springer, 357–379.Google Scholar
  4. Chouinard M, (2003) Système organisationnel et architecture d’un support d’information pour l’intégration des activités de logistique inversée au sein d’un centre de réadaptation. Mémoire de maîtrise, Université Laval, Québec, Canada, accessible at: Scholar
  5. Chouinard M, D’Amours S, Aït-Kadi D, (2005) Integration of reverse logistics activities within a supply chain information system. Computers in Industry, 56(1):105–124.CrossRefGoogle Scholar
  6. Côté M, Tremblay J, SOM Inc. (2003) Évaluation du projet de valorisation des aides à la locomotion. Régie de l’assurance maladie du Québec, Québec, Canada.Google Scholar
  7. Ernst R, Cohen MA, (1990) Operations related groups (ORGs): A clustering procedure for production inventory systems. Journal of Operations Management, 9(4):574–598.CrossRefGoogle Scholar
  8. Fandel G, Stammen M, (2003) A general model for extended strategic supply chain management with emphasis on product life cycles including development and recycling International Journal of Production Economics, 89(3):293–308.CrossRefGoogle Scholar
  9. Fleischmann M, (2001) Quantitative Models for Reverse Logistics. Springer, Berlin, Germany.zbMATHGoogle Scholar
  10. Flores BE, Olson DL, Dorai VK, (1992) Management of multi-criteria inventory classification. Mathematical and Computer Modeling, 16(12):71–82.zbMATHCrossRefGoogle Scholar
  11. Geoffrion AM, Graves GW, (1974) Multi-commodity distribution system design by Benders decomposition. Management Science, 20(5):822–844.CrossRefzbMATHMathSciNetGoogle Scholar
  12. Guide VDR (2000) Production planning and control for remanufacturing: Industry practice and research needs. Journal of Operations Management, 18:467–483.CrossRefGoogle Scholar
  13. Hillsman EL, Rhoda R, (1978) Errors in measuring distances from populations to services centers. Annals of the Regional Science Association, 12:74–88.CrossRefGoogle Scholar
  14. Jayaraman V, Patterson RA, Rolland E, (2003) The design of reverse distribution networks: Models and solution procedures. European Journal of Operational Research, 150:128–149.zbMATHCrossRefMathSciNetGoogle Scholar
  15. Jayaraman V, Pirkul H, (2001) Planning and coordination of production and distribution facilities for multiple commodities. European Journal of Operational Research, 133:394–408.zbMATHCrossRefGoogle Scholar
  16. Krikke H, (1998) Recovery Strategies and Reverse Logistics Network Design. PhD Thesis, University of Twente, Enschede, The Netherlands.Google Scholar
  17. Listes O, (2007) A generic stochastic model for supply-and-return network design. Computers and Operations Research, 34(2):417–442.zbMATHCrossRefGoogle Scholar
  18. Listes O, Dekker R, (2005) A stochastic approach to a case study for product recovery network design. European Journal of Operational Research, 160(1):268–287.zbMATHCrossRefGoogle Scholar
  19. Lu Z, Bostel N, (2007) A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Computers and Operations Research, 34(2):299–323.zbMATHCrossRefMathSciNetGoogle Scholar
  20. Martel A, (2001) Un modèle général pour l’optimisation de réseaux logistiques. Proceedings du 4 e Congrès international de génie industriel, 271–280.Google Scholar
  21. Martel A, (2004) Conception et gestion de chaîne logistique. Notes de cours, Université Laval, Québec, Canada.Google Scholar
  22. Ramanathan R, (2005) ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33:695–700.CrossRefGoogle Scholar
  23. Romanowski CJ, Nagi R, Sudit M, (2005) Data mining in an engineering design environment: OR applications from graph matching. Computers & Operations Research, 33:3150–3160.CrossRefGoogle Scholar
  24. Santoso T, Ahmed S, Goetschalckx M, Shapiro A, (2005) A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167:96–115.zbMATHCrossRefMathSciNetGoogle Scholar
  25. Shapiro JF (2001) Modeling the Supply Chain. Duxbury.Google Scholar
  26. Shih L-H (2001) Reverse logistics system planning for recycling electrical appliances and computers in Taiwan. Resources, Conservation and Recycling, 32:55–72.CrossRefGoogle Scholar
  27. Spengler T, Püchert H, Penkuhn T, Rentz O, (1997). Environmental integrated production and recycling management. European Journal of Operational Research, 97:308–326.zbMATHCrossRefGoogle Scholar
  28. Srinivasan M, Moon YB, (1999) A comprehensive algorithm for strategic analysis of supply chain networks. Computer and Industrial. Engineering, 36(3):615–633.CrossRefGoogle Scholar
  29. Teunter RH (2005) Determining optimal disassembly and recovery strategies. Omega. 34:533–537.CrossRefGoogle Scholar
  30. Thierry M, Salomon M, van Nunen J, van Wassenhove L, (1995) Strategic issues in product recovery management. California Management Review, 37(2):114–135.Google Scholar

Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  • Marc Chouinard
    • 1
  • Sophie D’Amours
    • 1
  • Daoud Aït-Kadi
    • 1
  1. 1.Centre de recherche sur les technologies de l’rganisation réseau (CENTOR), Département de génie mécaniqueUniversité LavalCanada

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