Skip to main content
SpringerLink
Log in

Inventory Routing Problem with Stochastic Demand and Lead Time: State of the Art

  • Conference paper
International Joint Conference SOCO’14-CISIS’14-ICEUTE’14

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 299))

Abstract

The integration of the different processes that conform the supply chain (SC) is fundamental to obtain a better coordination level. The inventory control and its distribution, are the processes that researches have found as the key in the loss of efficiency and effectiveness in the field of logistics, affecting so the synchronization in the SC management. In order to analyze the recent developments in the integration of these processes, this paper analyzes the state of the art of the progress in information management in the SC, the relationship of inventory policies and the demand information, modeling demand and use of optimization methods in the search for the appropriate solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Moin, N., Salhi, S.: Inventory routing problems: A logistical overview. Journal of the Operational Research Society 58(9), 1185–1194 (2007)

    Article  MATH  Google Scholar 

  2. Guasch, J., Kogan, J.: Inventories and logistic costs in developing countries: Levels and determinants – a red flag for competitiveness and growth. Revista de la Competencia y de la Propiedad Intelectual (2006)

    Google Scholar 

  3. Guasch, J.: Logistic costs in latin america and caribbean (2008)

    Google Scholar 

  4. Timme, S.G., Williams-Timme, C.: The real cost of holding inventory. Supply Chain Management Review 7, 30–37 (2003)

    Google Scholar 

  5. Gavirneni, S., Kapuscinski, R., Tayur, S.: Value of information in capacitated supply chains. Management Science 45(1), 16–24 (1999)

    Article  MATH  Google Scholar 

  6. Psaraftis, H.: Dynamic vehicle routing: Status and prospects. Annals of Operations Research 61(1), 143–164 (1995)

    Article  MATH  Google Scholar 

  7. Giard, V., Sali, M.: The bullwhip effect in supply chains: A study of contingent and incomplete literature. International Journal of Production Research 51(13), 3880–3893 (2013)

    Article  Google Scholar 

  8. Chopra, S., Meindl, P.: Supply Chain Management: Strategy, Planning, and Operation. Pearson international edition. Pearson Education, Limited (2012)

    Google Scholar 

  9. Wagner, M.: Inventory Routing: A Strategic Management Accounting Perspective. Hanken School of Economics (2011)

    Google Scholar 

  10. Wensing, T.: Periodic review inventory systems. Lecture Notes in Economics and Mathematical Systems, vol. 651 (2011)

    Google Scholar 

  11. Axsäter, S.: Evaluation of installation stock based (r, q)-policies for two-level inventory systems with poisson demand. Operations Research 46(3 suppl. 1), 135–145 (1998)

    Article  Google Scholar 

  12. Axsäter, S.: Exact analysis of continuous review (r,q) policies in two-echelon inventory systems with compound poisson demand. Operations Research 48(5), 686–696 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  13. Chao, X., Zhou, S.: Joint inventory-and-pricing strategy for a stochastic continuous-review system. IIE Transactions (Institute of Industrial Engineers) 38(5), 401–408 (2006)

    Google Scholar 

  14. Berling, P., Marklund, J.: Multi-echelon inventory control: an adjusted normal demand model for implementation in practice. International Journal of Production Research, 1–17 (article in press)

    Google Scholar 

  15. Saffari, M., Asmussen, S., Haji, R.: The m/m/1 queue with inventory, lost sale, and general lead times. Queueing Systems 75(1), 65–77 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  16. Schwarz, M., Sauer, C., Daduna, H., Kulik, R., Szekli, R.: M/m/1 queueing systems with inventory. Queueing Systems 54(1), 55–78 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  17. Saffari, M., Haji, R.: Queueing system with inventory for two-echelon supply chain. In: International Conference on Computers and Industrial Engineering, pp. 835–838 (2009)

    Google Scholar 

  18. Song, J.S., Zipkin, P.: Inventories with multiple supply sources and networks of queues with overflow bypasses. Management Science 55(3), 362–372 (2009)

    Article  MATH  Google Scholar 

  19. Song, J.S.: Effect of leadtime uncertainty in a simple stochastic inventory model. Management Science 40(5), 603–613 (1994)

    Article  MATH  Google Scholar 

  20. Labadie, N., Prins, C.: Vehicle routing nowadays: Compact review and emerging problems. In: Production Systems and Supply Chain Management in Emerging Countries: Best Practices, pp. 141–166. Springer (2012)

    Google Scholar 

  21. Reiman, M.I., Rubio, R., Wein, L.M.: Heavy traffic analysis of the dynamic stochastic inventory-routing problem. Transportation Science 4(33), 361–380 (1999)

    Article  Google Scholar 

  22. Kleywegt, A., Nori, V., Savelsbergh, M.: The stochastic inventory routing problem with direct deliveries. Transportation Science 36(1), 94–118 (2002)

    Article  MATH  Google Scholar 

  23. Bertazzi, L., Savelsbergh, M., Speranza, M.: Inventory routing. Operations Research/ Computer Science Interfaces Series 43, 49–72 (2008)

    Article  MathSciNet  Google Scholar 

  24. Rajesh Matai, S.S., Mittal, M.L.: Traveling Salesman Problem: an Overview of Applications, Formulations, and Solution Approaches. In: Traveling Salesman Problem, Theory and Applications. Intech (2010)

    Google Scholar 

  25. Toth, P., Vigo, D. (eds.): The Vehicle Routing Problem. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (2001)

    Google Scholar 

  26. Simić, D., Simić, S.: Evolutionary approach in inventory routing problem. In: Rojas, I., Joya, G., Cabestany, J. (eds.) IWANN 2013, Part II. LNCS, vol. 7903, pp. 395–403. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  27. Jaipuria, S., Mahapatra, S.: An improved demand forecasting method to reduce bullwhip effect in supply chains. Expert Systems with Applications 41(5), 2395–2408 (2014)

    Article  Google Scholar 

  28. Partovi, F., Anandarajan, M.: Classifying inventory using an artificial neural network approach. Computers and Industrial Engineering 41(4), 389–404 (2001)

    Article  Google Scholar 

  29. Christiansen, M., Fagerholt, K., Flatberg, T., Haugen, O., Kloster, O., Lund, E.H.: Maritime inventory routing with multiple products: A case study from the cement industry. European Journal of Operational Research 208(1), 86–94 (2011)

    Article  Google Scholar 

  30. Cheng, C.B., Wang, K.P.: Solving a vehicle routing problem with time windows by a decomposition technique and a genetic algorithm. Expert Systems with Applications 36(4), 7758–7763 (2009)

    Article  Google Scholar 

  31. Liu, S.C., Lee, W.T.: A heuristic method for the inventory routing problem with time windows. Expert Systems with Applications 38(10), 13223–13231 (2011)

    Article  Google Scholar 

  32. Qin, L., Miao, L., Ruan, Q., Zhang, Y.: A local search method for periodic inventory routing problem. Expert Systems with Applications 41(2), 765–778 (2014)

    Article  Google Scholar 

  33. Javid, A.A., Azad, N.: Incorporating location, routing and inventory decisions in supply chain network design. Transportation Research Part E: Logistics and Transportation Review 46(5), 582–597 (2010)

    Article  Google Scholar 

  34. Li, K., Chen, B., Sivakumar, A., Wu, Y.: An inventory-routing problem with the objective of travel time minimization. European Journal of Operational Research (2013)

    Google Scholar 

  35. Liu, S., Lin, C.: A heuristic method for the combined location routing and inventory problem. International Journal of Advanced Manufacturing Technology 26(4), 372–381 (2005)

    Article  Google Scholar 

  36. Sajjadi, S., Cheraghi, S.: Multi-products location-routing problem integrated with inventory under stochastic demand. International Journal of Industrial and Systems Engineering 7(4), 454–476 (2011)

    Google Scholar 

  37. Archetti, C., Doerner, K., Tricoire, F.: A heuristic algorithm for the free newspaper delivery problem. European Journal of Operational Research 230(2), 245–257 (2013)

    Article  MathSciNet  Google Scholar 

  38. Agra, A., Christiansen, M., Delgado, A., Simonetti, L.: Hybrid heuristics for a short sea inventory routing problem. European Journal of Operational Research (2013) (article in press)

    Google Scholar 

  39. Bertazzi, L., Bosco, A., Guerriero, F., Laganá, D.: A stochastic inventory routing problem with stock-out. Transportation Research Part C: Emerging Technologies 27, 89–107 (2013)

    Article  Google Scholar 

  40. Papageorgiou, D., Nemhauser, G., Sokol, J., Cheon, M.S., Keha, A.: Mirplib - a library of maritime inventory routing problem instances: Survey, core model, and benchmark results. European Journal of Operational Research 235(2), 350–366 (2013)

    Article  MathSciNet  Google Scholar 

  41. Corchado, E., Wozniak, M., Abraham, A., de Carvalho, A.C., Snásel, V.: Recent trends in intelligent data analysis. Neurocomputing 126, 1–2 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electronics and Computing Departament, Mondragon University, Goiru Kalea, 2, Arrasate, 20500, Spain

    Raúl Roldán & Rosa Basagoiti

  2. Compensar Unipanamericana Fundacin Universitaria Avenida (Calle), 32 No. 17 - 62, Bogot, D.C., Colombia

    Raúl Roldán

  3. University of Deusto, Deusto Institute of Technology (DeustoTech), Av. Universidades 24, Bilbao, 48007, Spain

    Enrique Onieva

Authors
  1. Raúl Roldán
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rosa Basagoiti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Enrique Onieva
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Raúl Roldán .

Editor information

Editors and Affiliations

  1. DeustoTech Computing, University of Deusto, Bilbao, Spain

    José Gaviria de la Puerta

  2. DeustoTech Computing, University of Deusto, Bilbao, Spain

    Iván García Ferreira

  3. DeustoTech Computing, University of Deusto, Bilbao, Spain

    Pablo Garcia Bringas

  4. German Workforce ADL Partnership Laboratory, Waltershausen, Germany

    Fanny Klett

  5. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Washington, USA

    Ajith Abraham

  6. Department of Computer Science, University of Sao Paulo at Sao Carlos, Sao Carlos, Brazil

    André C.P.L.F. de Carvalho

  7. Department of Civil Engineering Escuela Politénica Superior, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. Department of Civil Engineering Escuela Politénica Superior, University of Burgos, Burgos, Spain

    Bruno Baruque

  9. Departamento de Enxeñeria Industrial, Escuela Universitaria Politécnica, University of Salamanca, Salamanca, Spain and University of Coruña, La Coruña, Spain

    Héctor Quintián

  10. University of Salamanca, Salamanca, Spain

    Emilio Corchado

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Roldán, R., Basagoiti, R., Onieva, E. (2014). Inventory Routing Problem with Stochastic Demand and Lead Time: State of the Art. In: de la Puerta, J., et al. International Joint Conference SOCO’14-CISIS’14-ICEUTE’14. Advances in Intelligent Systems and Computing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-07995-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07995-0_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07994-3

  • Online ISBN: 978-3-319-07995-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation