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Multi-Product Multi Echelon Measurements of Perishable Supply Chain: Fuzzy Non-Linear Programming Approach

Author

Listed:
  • Sadia Samar Ali

    (Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Haripriya Barman

    (Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721102, India)

  • Rajbir Kaur

    (Government Girls College, Panchkula 134001, India)

  • Hana Tomaskova

    (Department of Information Technology, University of Hradec Králové, Rokitanského 62, 500 03 Hradec Králové, Czech Republic)

  • Sankar Kumar Roy

    (Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721102, India)

Abstract

The perishable milk products industry has to deal with multiple pressures such as demand forecasting, price fluctuations, lead time, order batching, and inflated orders along with difficulties of climatic and traffic conditions, storage areas and shipment in unfavorable circumstances. The Indian dairy industry faces immense wattage issue due to improper infrastructure for the cold chain storage facilities, resulting in unsatisfied customers. A study is undertaken to comprehend the supply chain framework that handles perishability issues in production and distribution. Researchers propose a multi-objective mixed-integer non-linear supply chain coordination model under uncertain environments to minimize the cost of transportation, offset wastage of products and neutralize the losses due to insufficiencies of transit and storage amenities. The proposed model is meant for managing the delivery with lesser deterioration losses for producers, warehouses, and retailers. The model considers various costs for holding, halting, discounts on purchased cost, transportation cost for truckload policy under regular and unforeseen circumstances of curfew, and identify the rate of deterioration to know the impact on the cost for all players involved in the SCM framework. To handle uncertainty of objective functions, fuzzy set concepts and the defuzzification method are imposed, and fuzzy non-linear programming algorithms are used to get the single objective function from the defuzzified multi-objective functions. Data analysis is done on Lingo 18.0 software. Rate of deterioration is highest for the warehouse, which indicates that efforts should be made to augment warehouse facilities for less spoilage to reduce losses in cost. Finally, the study ends with main findings, conclusions, limitations and future scopes.

Suggested Citation

  • Sadia Samar Ali & Haripriya Barman & Rajbir Kaur & Hana Tomaskova & Sankar Kumar Roy, 2021. "Multi-Product Multi Echelon Measurements of Perishable Supply Chain: Fuzzy Non-Linear Programming Approach," Mathematics, MDPI, vol. 9(17), pages 1-27, August.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:17:p:2093-:d:624937
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    References listed on IDEAS

    as
    1. Andrea Raiconi & Julia Pahl & Monica Gentili & Stefan Voß & Raffaele Cerulli, 2017. "Tactical Production and Lot Size Planning with Lifetime Constraints: A Comparison of Model Formulations," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(05), pages 1-24, October.
    2. 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.
    3. Itir Z. Karaesmen & Alan Scheller–Wolf & Borga Deniz, 2011. "Managing Perishable and Aging Inventories: Review and Future Research Directions," International Series in Operations Research & Management Science, in: Karl G. Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 393-436, Springer.
    4. Tai, Allen H. & Xie, Yue & Ching, Wai-Ki, 2016. "Inspection policy for inventory system with deteriorating products," International Journal of Production Economics, Elsevier, vol. 173(C), pages 22-29.
    5. Shilpy Tayal & S.R. Singh & Rajendra Sharma & Anand Chauhan, 2014. "Two echelon supply chain model for deteriorating items with effective investment in preservation technology," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 6(1), pages 84-105.
    6. Musen Xue & Wansheng Tang & Jianxiong Zhang, 2016. "Optimal dynamic pricing for deteriorating items with reference-price effects," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(9), pages 2022-2031, July.
    7. Pahl, Julia & Voß, Stefan, 2014. "Integrating deterioration and lifetime constraints in production and supply chain planning: A survey," European Journal of Operational Research, Elsevier, vol. 238(3), pages 654-674.
    8. Brahimi, Nadjib & Absi, Nabil & Dauzère-Pérès, Stéphane & Nordli, Atle, 2017. "Single-item dynamic lot-sizing problems: An updated survey," European Journal of Operational Research, Elsevier, vol. 263(3), pages 838-863.
    9. Stefano Coniglio & Arie M. C. A. Koster & Nils Spiekermann, 2018. "Lot sizing with storage losses under demand uncertainty," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 763-788, October.
    10. Yang, Hui-Ling, 2004. "Two-warehouse inventory models for deteriorating items with shortages under inflation," European Journal of Operational Research, Elsevier, vol. 157(2), pages 344-356, September.
    11. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    12. I. Nyoman Pujawan, 2004. "Assessing supply chain flexibility: a conceptual framework and case study," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 1(1), pages 79-97.
    13. Goswami, Adrijit & Chaudhuri, K. S., 1992. "Variations of order-level inventory models for deteriorating items," International Journal of Production Economics, Elsevier, vol. 27(2), pages 111-117, May.
    14. Maw-Sheng Chern & Ya-Lan Chan & Jinn-Tsair Teng, 2005. "A Comparison Among Various Inventory Shortage Models For Deteriorating Items On The Basis Of Maximizing Profit," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 121-134.
    15. Dye, Chung-Yuan & Hsieh, Tsu-Pang & Ouyang, Liang-Yuh, 2007. "Determining optimal selling price and lot size with a varying rate of deterioration and exponential partial backlogging," European Journal of Operational Research, Elsevier, vol. 181(2), pages 668-678, September.
    16. Angappa Gunasekaran & Nachiappan Subramanian & Shams Rahman, 2015. "Supply chain resilience: role of complexities and strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6809-6819, November.
    17. Ertogral, Kadir, 2008. "Multi-item single source ordering problem with transportation cost: A Lagrangian decomposition approach," European Journal of Operational Research, Elsevier, vol. 191(1), pages 156-165, November.
    18. 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.
    19. Qin, Yiyan & Wang, Jianjun & Wei, Caimin, 2014. "Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously," International Journal of Production Economics, Elsevier, vol. 152(C), pages 42-48.
    20. Kung-Jeng Wang & Yu-Siang Lin, 2012. "Optimal inventory replenishment strategy for deteriorating items in a demand-declining market with the retailer’s price manipulation," Annals of Operations Research, Springer, vol. 201(1), pages 475-494, December.
    21. Avi Herbon, 2018. "Optimal two-level piecewise-constant price discrimination for a storable perishable product," International Journal of Production Research, Taylor & Francis Journals, vol. 56(5), pages 1738-1756, March.
    22. Soni, Hardik N, 2013. "Optimal replenishment policies for non-instantaneous deteriorating items with price and stock sensitive demand under permissible delay in payment," International Journal of Production Economics, Elsevier, vol. 146(1), pages 259-268.
    23. Gupta, Yash P. & Somers, Toni M., 1992. "The measurement of manufacturing flexibility," European Journal of Operational Research, Elsevier, vol. 60(2), pages 166-182, July.
    24. Chung, Wenming & Talluri, Srinivas & Narasimhan, Ram, 2015. "Optimal pricing and inventory strategies with multiple price markdowns over time," European Journal of Operational Research, Elsevier, vol. 243(1), pages 130-141.
    25. Bernardo, John J. & Mohamed, Zubair, 1992. "The measurement and use of operational flexibility in the loading of Flexible Manufacturing Systems," European Journal of Operational Research, Elsevier, vol. 60(2), pages 144-155, July.
    26. Dobson, Gregory & Pinker, Edieal J. & Yildiz, Ozlem, 2017. "An EOQ model for perishable goods with age-dependent demand rate," European Journal of Operational Research, Elsevier, vol. 257(1), pages 84-88.
    27. Gong, Zhejun, 2008. "An economic evaluation model of supply chain flexibility," European Journal of Operational Research, Elsevier, vol. 184(2), pages 745-758, January.
    28. 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.
    29. Vernon Ning Hsu, 2000. "Dynamic Economic Lot Size Model with Perishable Inventory," Management Science, INFORMS, vol. 46(8), pages 1159-1169, August.
    30. Shah, Nita H. & Cárdenas-Barrón, Leopoldo Eduardo, 2015. "Retailer’s decision for ordering and credit policies for deteriorating items when a supplier offers order-linked credit period or cash discount," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 569-578.
    31. Pal, A.K. & Bhunia, A.K. & Mukherjee, R.N., 2006. "Optimal lot size model for deteriorating items with demand rate dependent on displayed stock level (DSL) and partial backordering," European Journal of Operational Research, Elsevier, vol. 175(2), pages 977-991, December.
    32. Gupta, Yash P. & Goyal, Sameer, 1989. "Flexibility of manufacturing systems: Concepts and measurements," European Journal of Operational Research, Elsevier, vol. 43(2), pages 119-135, November.
    33. Magfura Pervin & Sankar Kumar Roy & Gerhard-Wilhelm Weber, 2018. "Analysis of inventory control model with shortage under time-dependent demand and time-varying holding cost including stochastic deterioration," Annals of Operations Research, Springer, vol. 260(1), pages 437-460, January.
    34. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    35. Feng, Lin & Chan, Ya-Lan & Cárdenas-Barrón, Leopoldo Eduardo, 2017. "Pricing and lot-sizing polices for perishable goods when the demand depends on selling price, displayed stocks, and expiration date," International Journal of Production Economics, Elsevier, vol. 185(C), pages 11-20.
    36. Mendoza, Abraham & Ventura, José A., 2008. "Incorporating quantity discounts to the EOQ model with transportation costs," International Journal of Production Economics, Elsevier, vol. 113(2), pages 754-765, June.
    37. Behzadi, Golnar & O'Sullivan, Michael Justin & Olsen, Tava Lennon & Scrimgeour, Frank & Zhang, Abraham, 2017. "Robust and resilient strategies for managing supply disruptions in an agribusiness supply chain," International Journal of Production Economics, Elsevier, vol. 191(C), pages 207-220.
    38. Teng, Jinn-Tsair & Krommyda, Iris-Pandora & Skouri, Konstantina & Lou, Kuo-Ren, 2011. "A comprehensive extension of optimal ordering policy for stock-dependent demand under progressive payment scheme," European Journal of Operational Research, Elsevier, vol. 215(1), pages 97-104, November.
    39. Julia Pahl & Stefan Voß & David Woodruff, 2007. "Production planning with load dependent lead times: an update of research," Annals of Operations Research, Springer, vol. 153(1), pages 297-345, September.
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