As the industry environment becomes more competitive, the supply chain management for multi items has become an essential part of the industries. In this paper, a multi-echelon inventory model for deteriorating multi items with imperfect production has been developed under the environment of fuzzy and inflation. A single producer, multi-supplier, and multi-retailer are considered from the integrated point of view. Here, the producer only produces the retailer’s need to have a tremendous advantage and minimum loss. It is observed that the inflation rate is almost uncertain for deteriorating goods in every supply chain. In this paper, the inflation rate is taken as a triangular fuzzy number, and the centroid method is used to defuzzify the profit function. The shortage is not allowed in any part, an imperfect production process is considered, but it is not reworkable in this supply chain. Different inflation rates are considered for additional items because inflation has strained the most vulnerable consumers (the daily wage earners), who mainly demand goods in short and small quantities. This entire model is developed based on the retailer’s demand and due to which, the profit potential is maximized. The central premise of this study is to get maximum benefit by creating a production model for deterioration items. Finally, a numerical example and sensitivity analysis illustrate the present study. It is observed that if the number of shipments taken from the supplier increases during the production period, the total profit increases in crisp and fuzzy. If a positive change occurs in the number of shipments received through the producer to the retailer, then the fuzzy model has positive, but a slight negative change occurs in the crisp model. This paper shows the effect of a joint replenishment policy for multi-item compared with the independent approaches.
Keywords: Multi-echelon supply chain, multi items, inflation, triangular fuzzy number, imperfect production
@article{RO_2022__56_4_3071_0,
author = {Singh Padiyar, Surendra Vikram and Vandana and Bhagat, Naveen and Singh, Shiv Raj and Sarkar, Biswajit},
title = {Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment},
journal = {RAIRO. Operations Research},
pages = {3071--3096},
year = {2022},
publisher = {EDP-Sciences},
volume = {56},
number = {4},
doi = {10.1051/ro/2022071},
mrnumber = {4474352},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2022071/}
}
TY - JOUR AU - Singh Padiyar, Surendra Vikram AU - Vandana AU - Bhagat, Naveen AU - Singh, Shiv Raj AU - Sarkar, Biswajit TI - Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment JO - RAIRO. Operations Research PY - 2022 SP - 3071 EP - 3096 VL - 56 IS - 4 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2022071/ DO - 10.1051/ro/2022071 LA - en ID - RO_2022__56_4_3071_0 ER -
%0 Journal Article %A Singh Padiyar, Surendra Vikram %A Vandana %A Bhagat, Naveen %A Singh, Shiv Raj %A Sarkar, Biswajit %T Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment %J RAIRO. Operations Research %D 2022 %P 3071-3096 %V 56 %N 4 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2022071/ %R 10.1051/ro/2022071 %G en %F RO_2022__56_4_3071_0
Singh Padiyar, Surendra Vikram; Vandana; Bhagat, Naveen; Singh, Shiv Raj; Sarkar, Biswajit. Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment. RAIRO. Operations Research, Tome 56 (2022) no. 4, pp. 3071-3096. doi: 10.1051/ro/2022071
[1] , and , Inventory model for deteriorating items in green supply chain with credit period dependent demand. Int. J. Appl. Eng. Res. 15 (2020) 157–172.
[2] , Integrated two-stage inventory model for deteriorating items. Master’s Thesis, Chung Yuan Christian University Taiwan, ROC (2000).
[3] and , Optimal policies for multi echelon inventory problem. Manage. Sci. 6 (1960) 475–490. | DOI
[4] , and , Optimizing multi echelon inventory with three types of demand in supply chain. Transp. Res. Part E Logistic Transp. Rev. 107 (2017) 141–177. | DOI
[5] and , Triangular dense fuzzy sets and new defuzzification method. J. Intell. Fuzzy Syst. 31 (2016) 469–477. | Zbl
[6] and , A cloudy fuzzy economic quantity model for imperfect quality items with allowable proportionate discounts. J. Ind. Eng. Int. 15 (2019) 571–583. | DOI
[7] , and , Effects of variable setup cost, reliability, and production costs under controlled carbon emissions in a reliable production system. Euro. J. Indust. Eng. (2022). | DOI
[8] , and , Application of the artificial neural network with multithreading within an inventory model under uncertainty and inflation. Int. J. Fuzzy Syst. (2022). | DOI
[9] , and , A lot sizing model with partial downstream delayed payment, partial upstream advance payment, and partial backordering for deteriorating items. J. Manuf. Syst. 45 (2017) 322–342. | DOI
[10] , and , An optimal production inventory model for deteriorating items with multiple market demand. Eur. J. Oper. Res. 203 (2010) 593–600. | Zbl | DOI
[11] , , , , Fuzzy inventory model for deteriorating items with time varying demand and shortage. Am. J. Oper. Res. 2 (2012) 81–92.
[12] , , , and , A closed loop supply chain model with rework, Waste disposal, and carbon emission. Oper. Res. Perspect. 7 (2020) 100155. | MR
[13] , and , A study of an EOQ model under fuzzy demand rate. Int. Conf. Math. Comput. 834 (2018) 149–163. | MR | Zbl | DOI
[14] , and , An inventory control problem for deteriorating items with back-ordering and financial considerations under two levels of trade credit linked to order quantity. J. Ind. Manage. Optim. 12 (2016) 1091–1119. | MR | Zbl | DOI
[15] , and , Ordering policies for non-instantaneous deteriorating items under hybrid partial prepayment, partial trade credit and partial backordering. J. Oper. Res. Soc. 69 (2018) 1167–1196. | DOI
[16] , , and , A multi-stage sustainable production inventory model with carbon emission reduction and price dependent demand under stackelberg game. Appl. Sci. 10 (2020) 4878. | DOI
[17] , and , The inventory and pricing decisions in a three-echelon supply chain of deteriorating items under probabilistic environment. Transp. Res. Part E: Logistic Transp. Rev. 131 (2019) 118–138. | DOI
[18] and , A sustainable flexible manufacturing-remanufacturing model with improved service and green investment under variable demand. Exp. Syst. App. 202 (2022) 117154. | DOI
[19] , , and , Optimizing integrated manufacturing and products inspection policy for deteriorating manufacturing system with imperfect. J. Manuf. Syst. 37 (2015) 299–315. | DOI
[20] , and , Single-machine lot scheduling problem for deteriorating items with negative exponential deterioration rate. RAIRO: Oper. Res. 53 (2019) 1297–1307. | MR | Numdam | DOI
[21] , and , Inventory system with price dependent consumption for deteriorating items with shortages under fuzzy environment. Int. J. Sustainable Agr. Manage. Inf. 7 (2021) 218–231.
[22] , and , A credit policy approach in two warehouse inventory model for deteriorating items with price and stock dependent demand under partial backlogging. J. Ind. Eng. Int. 15 (2019) 147–170. | DOI
[23] , , and , An optimization of fuzzy EOQ model in healthcare industries with three different demand patterns using signed distance technique. Math. Eng. Sci. Aerosp. 10 (2019) 205–218.
[24] , and , Fuzzy EOQ model with reliability induced demand and defuzzification by Graded Mean Integration. In: Chapter in Book: Recent Advances in Mathematics for Engineering (2020) 305–326.
[25] and , A multi echelon supply chain inventory model with variable demand rate for deteriorating items. Pure Appl. Math. Sci. LXXIV (2011) 31–44.
[26] , Fuzzy inventory model for deterioration items in a supply chain system with price dependent demand and without backorder. Am. J. Eng. Res. 6 (2017) 183–187.
[27] and , A fuzzy inventory model with acceptable shortage using graded integration value method. J. Phys. Conf. Ser. 1000 (2018) 012009. | DOI
[28] , , , , and , A robust possibilistic flexible programming approach toward a resilient and cost-efficient biodiesel supply chain network. J. Clean. Prod. (2022) 132752. | DOI
[29] , and , Geometric programming solution of second degree difficulty for carbon ejection controlled reliable smart production system. RAIRO: Oper. Res. 56 (2022) 1013–1029. | MR | Zbl | Numdam | DOI
[30] , , and , Benefit of preservation technology with promotion and time-dependent deterioration under fuzzy learning. Exp. Syst. App. 201 (2022) 117169. | DOI
[31] , and , Supply chain model for perishable product under inflation and perishable delay in payment. Comput. Oper. Res. 27 (2000) 59–75. | Zbl | DOI
[32] and , A three echelon supply chain for economics growing quantity model with price and freshness dependent demand, pricing, ordering and shipment decisions. Oper. Res. Perspect. 7 (2020) 100153. | MR
[33] , , , and , An inventory model for deteriorating items with preservation facility of ramp type demand and trade credit. Int. J. Oper. Res. 17 (2020) 414–551. | MR | Zbl
[34] , and , A reverse logistics inventory model with multiple production and remanufacturing batches under fuzzy environment. RAIRO: Oper. Res. 55 (2021) 571–588. | MR | Zbl | Numdam | DOI
[35] and , Inventory model for deterioration items involving fuzzy with shortage and exponential demand. Int. J. Supply Oper. Manage. 2 (2015) 888–904.
[36] and , Replenishment policy for deteriorating items with trade credit and allowable shortage under inflationary environment. Int. J. Process Manage. Benchmarking 10 (2020) 462–478. | DOI
[37] , and , Three stage supply chain model with two warehouse, imperfect production, variable demand rate and inflation. Int. J. Ind. Eng. Comput. 4 (2013) 81–92.
[38] , and , Analysis of three level supply chain of inventory with deteriorating for muti-items. Int. J. Ind. Eng. Comput. 5 (2014) 417–430.
[39] , and , Two levels of storage model for deteriorating items stock dependent demand and partial backlogging with both rented warehouse. Int. J. Process Manage. Benchmarking 9 (2019) 485–498. | DOI
[40] , An economic order quantity model for deteriorating item in a purchasing system with multiple prepayments. Appl. Math. Modell. 38 (2014) 5357–5366. | MR | Zbl | DOI
[41] and , An inventory control problem for deteriorating items with back-ordering and financial considerations. Appl. Math. Modell. 38 (2014) 93–109. | MR | Zbl | DOI
[42] and , Pricing and lot sizing of a decaying item under group dispatching with time-dependent demand and decay rates. Sci. Iran. 25 (2018) 1656–1670.
[43] , and , Revisiting a fuzzy rough economic order quantity model for deteriorating items considering quantity discount and prepayment. Math. Comput. Modell. 57 (2013) 1466–1479. | MR | DOI
[44] , and , Joint optimization of price, replenishment frequency, replenishment cycle and production rate in vendor managed inventory system with deteriorating items. Int. J. Prod. Econ. 159 (2015) 285–295. | DOI
[45] , and , Optimal multi-discount selling prices schedule for deteriorating product. Sci. Iran. 22 (2015) 2595–2603.
[46] , and , Partial linked-to-order delayed payment and lifetime effects on decaying items ordering. Oper. Res. 21 (2021) 2077–2099.
[47] , and , Developing EOQ model with instantaneous deteriorating items for a vendor-managed inventory (VMI) system. J. Ind. Syst. Eng. 7 (2014) 21–42.
[48] and , An EOQ model for decaying item with full advanced payment and conditional discount. Ann. Oper. Res. 259 (2017) 415–436. | MR | Zbl | DOI
[49] , , , and , Controlling defective items in a complex multi-phase manufacturing system. RAIRO: Oper. Res. 56 (2022) 871–889. | MR | Zbl | Numdam | DOI
[50] and , Integrated vendor buyer inventory model in a supply chain with variable lead time and setup cost reduction. Int. J. Process Manage. Benchmarking 9 (2019) 324–350. | DOI
[51] , and , Environmental and economic sustainability through innovative green products by remanufacturing. J. Clean. Prod. 332 (2022) 129813. | DOI
[52] , , , and , Impact of energy and carbon emission of a supply chain management with two level trade credit policy. Energies 14 (2021) 1569. | DOI
[53] , , and , Reduction of pollution through sustainable and flexible production by controlling by-products. J. Env. Inform. (2022). http://www.jeionline.org/index.php?journal=mys&page=article&op=view&path%5B%5D=202200476
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