A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 217-239.

This research work derives an integrated inventory model for imperfect production/remanufacturing process with time varying demand, production and repair rates under inflationary environment. This inventory model deals with the joint manufacturing and remanufacturing options. There is a collection process devoted to collect used items with the aim to remanufacture them. Both production and repair runs generate imperfect items. The repair process remanufactures used and imperfect items. Further, it is also considered that the remanufactured item that is classified as good has exactly same quality as that of new one. Demand rate is supposed as time dependent. The production rate is assumed to be demand dependent and therefore it is also time dependent. The repair rate is supposed to be a function of time. All system costs are contemplated in uncertain environment. Therefore, the costs are considered as fuzzy nature. Theoretical results are illustrated thru a numerical example. Finally, a sensitivity analysis is performed in order to know the impact of different parameters on the optimal policy.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017070
Classification : 90B05
Mots clés : Imperfect production, time dependent demand, production and repair rates, reverse logistics, inflation, fuzzy costs
Jain, Shalini 1 ; Tiwari, Sunil 1 ; Cárdenas-Barrón, Leopoldo Eduardo 1 ; Shaikh, Ali Akbar 1 ; Singh, Shiv Raj 1

1
@article{RO_2018__52_1_217_0,
     author = {Jain, Shalini and Tiwari, Sunil and C\'ardenas-Barr\'on, Leopoldo Eduardo and Shaikh, Ali Akbar and Singh, Shiv Raj},
     title = {A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {217--239},
     publisher = {EDP-Sciences},
     volume = {52},
     number = {1},
     year = {2018},
     doi = {10.1051/ro/2017070},
     mrnumber = {3812478},
     zbl = {1397.90022},
     language = {en},
     url = {http://www.numdam.org/articles/10.1051/ro/2017070/}
}
TY  - JOUR
AU  - Jain, Shalini
AU  - Tiwari, Sunil
AU  - Cárdenas-Barrón, Leopoldo Eduardo
AU  - Shaikh, Ali Akbar
AU  - Singh, Shiv Raj
TI  - A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions
JO  - RAIRO - Operations Research - Recherche Opérationnelle
PY  - 2018
SP  - 217
EP  - 239
VL  - 52
IS  - 1
PB  - EDP-Sciences
UR  - http://www.numdam.org/articles/10.1051/ro/2017070/
DO  - 10.1051/ro/2017070
LA  - en
ID  - RO_2018__52_1_217_0
ER  - 
%0 Journal Article
%A Jain, Shalini
%A Tiwari, Sunil
%A Cárdenas-Barrón, Leopoldo Eduardo
%A Shaikh, Ali Akbar
%A Singh, Shiv Raj
%T A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions
%J RAIRO - Operations Research - Recherche Opérationnelle
%D 2018
%P 217-239
%V 52
%N 1
%I EDP-Sciences
%U http://www.numdam.org/articles/10.1051/ro/2017070/
%R 10.1051/ro/2017070
%G en
%F RO_2018__52_1_217_0
Jain, Shalini; Tiwari, Sunil; Cárdenas-Barrón, Leopoldo Eduardo; Shaikh, Ali Akbar; Singh, Shiv Raj. A fuzzy imperfect production and repair inventory model with time dependent demand, production and repair rates under inflationary conditions. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 217-239. doi : 10.1051/ro/2017070. http://www.numdam.org/articles/10.1051/ro/2017070/

[1] A. Alamri, Theory and methodology on the global optimal solution to a general reverse logistics inventory model for deteriorating items and time-varying rates. Comput. Ind. Eng. 60 (2011) 236–247. | DOI

[2] L. Benkherouf and M. Omar, Optimal manufacturing batch size with rework for a finite-horizon time-varying demand rates inventory model. RAIRO: OR 51 (2017) 173–187. | DOI | Numdam | MR | Zbl

[3] L.E. Cárdenas-Barrón, B. Sarkar and G. Treviño-Garza, Easy and improved algorithms to joint determination of the replenishment lot size and number of shipments for an EPQ model with rework. Math. Comput. Appl. 18 (2016) 132–138. | Zbl

[4] H.C. Chang, An application of fuzzy sets theory to the EOQ model with imperfect quality items. Comput. Oper. Res. 31 (2004) 2079–2092. | DOI | MR | Zbl

[5] C.J. Chung and H.M. Wee, Green-component life-cycle value on design and reverse manufacturing in semi-closed supply chain. Int. J. Prod. Econ. 113 (2008) 528–545. | DOI

[6] C.J. Chung and H.M. Wee, Short life-cycle deteriorating product remanufacturing in a green supply chain inventory control system. Int. J. Prod. Econ. 129 (2011) 195–203. | DOI

[7] I. Dobos and K. Richter, A production/recycling model with stationary demand and return rates. Cent. Eur. J. Oper. Res. 11 (2003) 35–46. | MR | Zbl

[8] I. Dobos and K. Richter, An extended production/recycling model with stationary demand and return rates. Int. J. Prod. Econ. 90 (2004) 311–323. | DOI

[9] I. Dobos and K. Richter, A production/recycling model with quality considerations. Int. J. Prod. Econ. 104 (2006) 571–579. | DOI

[10] A.M.A. El Saadany, and M.Y. Jaber, A production/remanufacturing inventory model with price and quality dependent return rate. Comput. Ind. Eng. 58 (2010) 352–362. | DOI

[11] C.F. Hsueh, An inventory control model with consideration of remanufacturing and product life cycle. Int. J. Prod. Econ. 133 (2011) 645–652. | DOI

[12] https://en.wikipedia.org/wiki/Reverse_logistics.

[13] K. Inderfurth, G. Lindner and N.P. Rachaniotis, Lot sizing in a production system with rework and product deterioration. Int. J. Prod. Res. 43 (2005) 1355–1374. | DOI | Zbl

[14] M.Y. Jaber and A.M.A. El Saadany The production, remanufacture and waste disposal model with lost sales. Int. J. Prod. Econ. 120 (2009) 115–124. | DOI

[15] M.Y. Jaber and A.M.A. El Saadany An economic production and remanufacturing model with learning effects. Int. J. Prod. Econ. 131 (2011) 115–127. | DOI

[16] M.Y. Jaber and M.A. Rosen, The economic order quantity repair and waste disposal model with entropy cost. Eur. J. Oper. Res. 188 (2008) 109–120. | DOI | Zbl

[17] A. Kaufmann and M. Gupta, Introduction to Fuzzy Arithmetic: Theory and Applications. Van Nostrand Reinhold, New York (1991). | Zbl

[18] M.S. Kim and B. Sarkar, Multi-stage cleaner production process with quality improvement and lead time dependent ordering cost. J. Clean. Prod. 144 (2017) 572–590. | DOI

[19] A.I. Kokkinaki, R. Dekker, J. Van Nunen, and C. Pappis, Integrating a Web-Based System With Business Processes in Closed Loop Supply Chains. [Electronic version], Econometric Institute Report Series, EI2001-31, Erasmus University, Rotterdam (2001) 1–30.

[20] I. Konstantaras and S. Papachristos, Lot-sizing for a single-product recovery system with backordering. Int. J. Prod. Res. 44 (2004) 2031–2045. | DOI | Zbl

[21] I. Konstantaras and S. Papachristos, Optimal policy and holding cost stability regions in a periodic review inventory system with manufacturing and remanufacturing options. Eur. J. Oper. Res. 178 (2007) 433–448. | DOI | Zbl

[22] I. Konstantaras and S. Papachristos, A note on: developing an exact solution for an inventory system with product recovery. Int. J. Prod. Econ. 111 (2008) 707–712. | DOI

[23] I. Konstantaras, and S. Papachristos, Note on: an optimal ordering and recovery policy for reusable items. Comput. Ind. Eng. 55 (2008) 729–734. | DOI

[24] I. Konstantaras and K. Skouri, Lot sizing for a single product recovery system with variable setup numbers. Eur. J. Oper. Res. 203 (2010) 326–335. | DOI | Zbl

[25] I. Konstantaras, K. Skouri and M.Y. Jaber, Lot sizing for a recoverable product with inspection and sorting. Comput. Ind. Eng. 58 (2010) 452–462. | DOI

[26] S. Nahmias, H.A. Rivera, Deterministic model for a repairable inventory system with a finite repair rate. Int. J. Prod. Res. 17 (1979) 215–221. | DOI

[27] M. Omar, I. Yeo, A model for a production-repair system under a time-varying demand process. Int. J. Prod. Econ. 119 (2009) 17–23. | DOI

[28] M. Omar, I. Yeo, A production and repair model under a time-varying demand process. Bull. Malay. Math. Sci. Soc. 35 (2012) 85–100. | MR | Zbl

[29] K. Richter, The EOQ repair and waste disposal model with variable setup numbers. Eur. J. Oper. Res. 95 (1996) 313–324. | DOI | Zbl

[30] K. Richter, The extended EOQ repair and waste disposal model. Int. J. Prod. Econ.45 (1996), 443–447. | DOI

[31] K. Richter, Pure and mixed strategies for the EOQ repair and waste disposal problem. OR Spectr. 19 (1997) 123–129. | DOI | MR | Zbl

[32] D.S. Rogers and R.S. Tibben-Lembke, Going Backwards: Reverse Logistics Trends and Practices. Reverse Logistics Executive Council (1998).

[33] B. Sarkar and A.S. Mahapatra, Periodic review fuzzy inventory model with variable lead time and fuzzy demand. To appear in: Int. Trans. Oper. Res. DOI: (2015). | DOI | MR

[34] B. Sarkar and I. Moon, Improved quality, setup cost reduction, and variable backorder costs in an imperfect production process. Int. J. Prod. Econ. 155 (2014) 204–213. | DOI

[35] B. Sarkar and S. Saren, Product inspection policy for an imperfect production system with inspection errors and warranty cost. Eur. J. Oper. Res. 248 (2016) 263–271. | DOI | Zbl

[36] B. Sarkar, L.E. Cárdenas-Barrón, M. Sarkar and M.L. Singgih, An economic production quantity model with random defective rate, rework process and backorders for a single stage production system. J. Manuf. Syst. 33 (2014) 423–435. | DOI

[37] D.A. Schrady, A deterministic inventory model for repairable items. Nav. Res. Logist. Q. 14 (1967) 391–398. | DOI

[38] S.R. Singh and N. Saxena, A closed loop supply chainsystem with flexible manufacturing and reverse logistics operationunder shortagesfor deteriorating items. Procedia Technol. 10 (2013) 330–339. | DOI

[39] A.A. Taleizadeh, S.T.A. Niaki, and M.B. Aryanezhad, A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments. Math. Comput. Model. 49 (2009) 1044–1057. | DOI | MR | Zbl

[40] A. Taleizadeh, A.A. Najafi and S.A. Niaki, Economic production quantity model with scrapped items and limited production capacity. Sci. Iran. Trans. E Ind. Eng. 17 (2010) 58–69.

[41] A.A. Taleizadeh, F. Barzinpour and H.M. Wee, Meta-heuristic algorithms for solving a fuzzy single-period problem. Math. Comput. Model. 54 (2011) 1273–1285. | DOI | MR | Zbl

[42] A.A. Taleizadeh, S.T.A. Niaki, R.G. Meibodi, Replenish-up-to multi-chance-constraint inventory control system under fuzzy random lost-sale and backordered quantities. Knowl.-Based Syst. 53 (2013) 147–156. | DOI

[43] A.A. Taleizadeh, L.E. Cárdenas-Barrón and B. Mohammadi, A deterministic multi product single machine EPQ model with backordering, scraped products, rework and interruption in manufacturing process. Int. J. Prod. Econ. 150 (2014) 9–27. | DOI

[44] M. Tayyab and B. Sarkar, Optimal batch quantity in a cleaner multi-stage lean production system with random defective rate. J. Clean. Prod. 139 (2016) 922–934. | DOI

[45] J.S. Yao and K. Wu, Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets Syst. 116 (2000) 275–288. | DOI | MR | Zbl

Cité par Sources :