IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v131y2011i1p421-429.html
   My bibliography  Save this article

An optimization approach for managing fresh food quality throughout the supply chain

Author

Listed:
  • Rong, Aiying
  • Akkerman, Renzo
  • Grunow, Martin

Abstract

One of the most challenging tasks in today's food industry is controlling the product quality throughout the food supply chain. In this paper, we integrate food quality in decision-making on production and distribution in a food supply chain. We provide a methodology to model food quality degradation in such a way that it can be integrated in a mixed-integer linear programming model used for production and distribution planning. The resulting model is applied in an illustrative case study, and can be used to design and operate food distribution systems, using both food quality and cost criteria.

Suggested Citation

  • Rong, Aiying & Akkerman, Renzo & Grunow, Martin, 2011. "An optimization approach for managing fresh food quality throughout the supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 421-429, May.
  • Handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:421-429
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(09)00429-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ravindra K. Ahuja & Wei Huang & H. Edwin Romeijn & Dolores Romero Morales, 2007. "A Heuristic Approach to the Multi-Period Single-Sourcing Problem with Production and Inventory Capacities and Perishability Constraints," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 14-26, February.
    2. Trienekens, Jacques & Zuurbier, Peter, 2008. "Quality and safety standards in the food industry, developments and challenges," International Journal of Production Economics, Elsevier, vol. 113(1), pages 107-122, May.
    3. Spitter, J. M. & Hurkens, C. A. J. & de Kok, A. G. & Lenstra, J. K. & Negenman, E. G., 2005. "Linear programming models with planned lead times for supply chain operations planning," European Journal of Operational Research, Elsevier, vol. 163(3), pages 706-720, June.
    4. Niemi, Petri & Pekkanen, Petra & Huiskonen, Janne, 2007. "Improving the impact of quantitative analysis on supply chain policy making," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 165-175, July.
    5. Danny C. Myers, 1997. "Meeting seasonal demand for products with limited shelf lives," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(5), pages 473-483, August.
    6. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    7. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    2. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    3. Agustina, Dwi & Lee, C.K.M. & Piplani, Rajesh, 2014. "Vehicle scheduling and routing at a cross docking center for food supply chains," International Journal of Production Economics, Elsevier, vol. 152(C), pages 29-41.
    4. V. Radhamani & B. Sivakumar & G. Arivarignan, 2022. "A Comparative Study on Replenishment Policies for Perishable Inventory System with Service Facility and Multiple Server Vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 229-265, March.
    5. Ketzenberg, M.E. & Bloemhof-Ruwaard, J.M., 2009. "The Value of RFID Technology Enabled Information to Manage Perishables," ERIM Report Series Research in Management ERS-2009-020-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Lodree Jr., Emmett J. & Uzochukwu, Benedict M., 2008. "Production planning for a deteriorating item with stochastic demand and consumer choice," International Journal of Production Economics, Elsevier, vol. 116(2), pages 219-232, December.
    7. Ketzenberg, Michael & Oliva, Rogelio & Wang, Yimin & Webster, Scott, 2023. "Retailer inventory data sharing in a fresh product supply chain," European Journal of Operational Research, Elsevier, vol. 307(2), pages 680-693.
    8. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    9. Li‐Ming Chen & Amar Sapra, 2013. "Joint inventory and pricing decisions for perishable products with two‐period lifetime," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(5), pages 343-366, August.
    10. Omar Ahumada & J. Villalobos, 2011. "A tactical model for planning the production and distribution of fresh produce," Annals of Operations Research, Springer, vol. 190(1), pages 339-358, October.
    11. R Bai & E K Burke & G Kendall, 2008. "Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1387-1397, October.
    12. J-M Chen & L-T Chen, 2004. "Pricing and lot-sizing for a deteriorating item in a periodic review inventory system with shortages," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 892-901, August.
    13. Wang, X. & Li, D. & O'brien, C. & Li, Y., 2010. "A production planning model to reduce risk and improve operations management," International Journal of Production Economics, Elsevier, vol. 124(2), pages 463-474, April.
    14. Stratos Ioannidis & Oualid Jouini & Angelos Economopoulos & Vassilis Kouikoglou, 2013. "Control policies for single-stage production systems with perishable inventory and customer impatience," Annals of Operations Research, Springer, vol. 209(1), pages 115-138, October.
    15. S. Panda & S. Saha & M. Basu, 2009. "An EOQ model for perishable products with discounted selling price and stock dependent demand," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 17(1), pages 31-53, March.
    16. Yadavalli, V.S.S. & Sivakumar, B. & Arivarignan, G., 2008. "Inventory system with renewal demands at service facilities," International Journal of Production Economics, Elsevier, vol. 114(1), pages 252-264, July.
    17. I. Padmavathi & A. Shophia Lawrence & B. Sivakumar, 2016. "A finite-source inventory system with postponed demands and modified M vacation policy," OPSEARCH, Springer;Operational Research Society of India, vol. 53(1), pages 41-62, March.
    18. Ting, Pin-Shou, 2015. "Comments on the EOQ model for deteriorating items with conditional trade credit linked to order quantity in the supply chain management," European Journal of Operational Research, Elsevier, vol. 246(1), pages 108-118.
    19. Feng, Lin & Wang, Wan-Chih & Teng, Jinn-Tsair & Cárdenas-Barrón, Leopoldo Eduardo, 2022. "Pricing and lot-sizing decision for fresh goods when demand depends on unit price, displaying stocks and product age under generalized payments," European Journal of Operational Research, Elsevier, vol. 296(3), pages 940-952.
    20. Beullens, Patrick & Ghiami, Yousef, 2022. "Waste reduction in the supply chain of a deteriorating food item – Impact of supply structure on retailer performance," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1017-1034.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:421-429. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.