A Location-Routing-Inventory Model for Perishable Items Using Fresher First and Older First Inventory Management Policies
محورهای موضوعی : Inventory ManagementShima Harati 1 , Emad Roghanian 2 , Ashkan Hafezalkotob 3 , Amir Abbas Shojaie 4
1 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
4 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
کلید واژه: perishable items, routing, Inventory locating, Inventory management policy,
چکیده مقاله :
The purpose of the current research is to present a location-routing-inventory model for perishable products. The presented model is applied in a two-stage structure. The first-stage decisions confirm the establishment of distribution centers, whereas the second-stage decisions determine the other variables of the problem. For a better management of inventory, it has been used under the names of fresher first and older first policies. In the fresher first policy, the fresher items have a priority to be sent to the customer, whereas in the older first policy, the items with a longer age have the priority to be sent to the customer. The summary of the results of the models demonstrates that among the free, fresher first, and older first policies, it is the free policy that offers a higher profit function to the customer than the other two policies since it is more flexible and general,and encompasses these two extremes. The free policy lets the model determine which items to sell at any given time period in order to maximize profit.Moreover, in the older first policy, since the older items reach the customers sooner than the other items, the number of the expired items is reduced. However, this policy brings the lowest revenue to the customer. In the fresher first policy, since the fresher items are sold first and then the older items are sold, the number of the expired items is increased along the customer horizon. Nevertheless, the customer obtains more revenue compared with the older first policy.
investment strategy for perishable foods with price-quality dependent
demand. Annals of Operations Research, 226(1), 397-416.
[2] Shah, N. H. (2017). Three-layered integrated inventory model for
deteriorating items with quadratic demand and two-level trade credit
financing. International Journal of Systems Science: Operations &
Logistics, 4(2), 85-91.
food supply chains with stochastic demands: A multi-period inventory
routing problem with perishable products. Simulation Modelling
Practice and Theory, 97, 101970.
buyers production–inventory policy for a deteriorating item. European
Journal of Operational Research, 143(3), 570-581.
for deteriorating items under a multi-echelon supply chain
environment. International journal of production economics, 86(2),
155-168.
optimization model for green closed-loop supply chain network design
of perishable goods. Journal of Cleaner Production, 226, 282-305.
production and distribution planning of perishable products with
inventory and routing considerations. Mathematical Problems in
Engineering, 2014 (10), 1-10.
pricing and deteriorating model and a hybrid algorithm for a VMI
(vendor-managed-inventory) supply chain. IEEE Transactions on
Automation Science and Engineering, 8(4), 673-682.
based simulated annealing algorithm for the multi-product multi-
retailer perishable inventory routing problem. Computers & Industrial
Engineering, 99, 189-201.
[10] Hsu, C. I., Hung, S. F., & Li, H. C. (2007). Vehicle routing problem
with time-windows for perishable food delivery. Journal of food
engineering, 80(2), 465-475.
[11] Seyedhosseini, S. M., MahdaviMazdeh, M., Makui, A., &Ghoreyshi,
S. M. (2016). An inventory routing problem for perishable products
with stochastic demands and direct deliveries. International Journal of
Industrial Engineering & Production Research, 27(1), 21-30.
[12] Chao, C., Zhihui, T., &Baozhen, Y. (2019). Optimization of two-stage
location–routing–inventory problem with time-windows in food
distribution network. Annals of Operations Research, 273(1-2), 111-
134.
[13] Khalili-Damghani, K., Abtahi, A. R., & Ghasemi, A. (2015). A new bi-
objective location-routing problem for distribution of perishable
products: evolutionary computation approach. Journal of Mathematical
Modelling and Algorithms in Operations Research, 14(3), 287-312.
[14] S. Axs¨ater. Inventory control. International Series in Operations
Research & Management Science, volume 90. Springer, New York,
2006.
[15] S. Nahmias. Perishable Inventory Systems. International Series in
Operations Research & Management Science, volume 160. Springer,
New York, 2011.
[16] R. Haijema. A new class of stock-level dependent ordering policies
for perishables with a short maximum shelf life. International Journal
of Production Economics, forthcoming, 2011.
[17] S. Minner and S. Transchel. Periodic review inventory-control for
perishable products under service-level constraints. OR Spectrum,
32(4):979–996, 2010.
[18] Z. Karaesmen, A. Scheller-Wolf, and B. Deniz. Managing perishable
and aging inventories: Review and future research directions. In K. G.
Kempf, P. Keskinocak, and R. Uzsoy, editors, Planning Production
and Inventories in the Extended Enterprise, volume 151 of
International Series in Operations Research & Management Science,
pages 393–436. Springer, New York, 2011.
[19] Nagurney, M. Yu, A. H. Masoumi, and L. S. Nagurney. Networks
against Time − Supply Chain Analytics for Perishable Products.
Springer, New York, 2013.
[20] H. Andersson, A. Hoff, M. Christiansen, G. Hasle, and A.
Lّ kketangen. Industrial aspects and literature survey: Combined
inventory management and routing. Computers & Operations
Research, 37(9):1515–1536, 2010.
[21] L. C. Coelho, J.-F. Cordeau, and G. Laporte. Thirty years of
inventory-routing. Transportation Science, forthcoming, 2014. doi:
10.1287/trsc.2013.0472.
[22] Leandro C. Coelho, Gilbert Laporte. (2014). Optimal Joint
Replenishment, Delivery and Inventory Management Policies for
Perishable Products, Computers & Operations Research, 47, 42–52.
[23] Axsäter, S. (2006). Planning order releases for an assembly system
with random operation times. In Stochastic Modeling of
Manufacturing Systems (pp. 333-344). Springer, Berlin, Heidelberg.
[24] Raafat, F., Wolfe, P. M., & Eddin, H. K. (1991). An inventory model
for deteriorating items. Computers and Industrial Engineering, 20(1),
89-94.
[25] Moghaddam, S. T., Javadi, M., & Molana, S. M. H. (2019). A reverse
logistics chain mathematical model for a sustainable production
system of perishable goods based on demand optimization. Journal of
Industrial Engineering International, 15(4), 709-721.
[26] Panda, G. C., Khan, M. A. A., & Shaikh, A. A. (2019). A credit policy
approach in a two-warehouse inventory model for deteriorating items
with price-and stock-dependent demand under partial backlogging.
Journal of Industrial Engineering International, 15(1), 147-170.
[27] Abou Chakra, H., & Ashi, A. (2019). Comparative analysis of
design/build and design/bid/build project delivery systems in Lebanon.
Journal of Industrial Engineering International, 15(1), 147-152.
[28] Saeidi, R.G., Amin, G.R., Raissi, S. et al. An efficient DEA method for
ranking woven fabric defects in textile manufacturing. Int J Adv Manuf
Technol 68, 349–354 (2013). https://doi.org/10.1007/s00170-013-
4732-4