Open Access
Issue |
RAIRO-Oper. Res.
Volume 56, Number 6, November-December 2022
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Page(s) | 4251 - 4280 | |
DOI | https://doi.org/10.1051/ro/2022145 | |
Published online | 21 December 2022 |
- H. Barman, M. Pervin, S.K. Roy and G.W. Weber, Back-ordered inventory model with inflation in a cloudy-fuzzy environment. J. Ind. Manag. Optim. 17 (2021) 1913. [MathSciNet] [Google Scholar]
- S.P. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, New York (2004). [CrossRef] [Google Scholar]
- S.C. Das, A.K. Manna, M.S. Rahman, A.A. Shaikh and A.K. Bhunia, An inventory model for non-instantaneous deteriorating items with preservation technology and multiple credit periods-based trade credit financing via particle swarm optimization. Soft Comput. 25 (2021) 5365–5384. [CrossRef] [Google Scholar]
- S.K. De and G.C. Mahata, A profit jump inventory model for imperfect quality items with receiving reparative batch and order overlapping in dense fuzzy environment. Revue d’Orthopdie Dento-Faciale 55 (2021). [Google Scholar]
- C.Y. Dye and T.P. Hsieh, An optimal replenishment policy for deteriorating items with effective investment in preservation technology. Eur. J. Oper. Res. 218 (2012) 106–112. [Google Scholar]
- T. Garai, D. Chakraborty and T.K. Roy, Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables. J. Intell. Fuzzy Syst. 36 (2019) 3725–3738. [CrossRef] [Google Scholar]
- C.H. Glock, K. Schwindl and M.Y. Jaber, An EOQ model with fuzzy demand and learning in fuzziness. Int. J. Serv. Oper. Manag. 12 (2012) 90–100. [Google Scholar]
- M.S. Habib, M. Omair, M.B. Ramzan, T.N. Chaudhary, M. Farooq and B. Sarkar, A robust possibilistic flexible programming approach toward a resilient and cost-efficient biodiesel supply chain network, J. Clean. Prod. 366 (2022) 132752. [CrossRef] [Google Scholar]
- C.K. Jaggi, A. Sharma and R. Jain, Fuzzification of EOQ model under the condition of permissible delay in payments. Int. J. Strateg. Decis. Sci. 3 (2012) 1–19. [CrossRef] [Google Scholar]
- M.Y. Jani, M.R. Betheja, U. Chaudhari and B. Sarkar, Optimal investment in preservation technology for variable demand under trade-credit and shortages. Mathematics 9 (2021) 1301. [CrossRef] [Google Scholar]
- M.A.A. Khan, A.A. Shaikh, G. Panda, I. Konstantaras and L.E. Cárdenas-Barrón, The effect of advance payment with discount facility on supply decisions of deteriorating products whose demand is both price and stock dependent. Int. Trans. Oper. Res. 27 (2020) 1343–1367. [CrossRef] [MathSciNet] [Google Scholar]
- B.A. Kumar and S.K. Paikray, Cost optimization inventory model for deteriorating items with trapezoidal demand rate under completely backlogged shortages in crisp and fuzzy environment. RAIRO: OR 56 (2022) 1969–1994. [CrossRef] [EDP Sciences] [Google Scholar]
- S. Kumar, M. Sigroha, K. Kumar and B. Sarkar, Manufacturing/remanufacturing based supply chain management under advertisements and carbon emission process. RAIRO: OR (2022). [Google Scholar]
- J.J. Liao, K.N. Huang, K.J. Chung, S.D. Lin, S.T. Chuang and H.M. Srivastava, Optimal ordering policy in an economic order quantity (EOQ) model for non-instantaneous deteriorating items with defective quality and permissible delay in payments. Rev. Real Acad. Cienc. Exactas Fis. Nat. Ser. A: Mat. 114 (2020) 1–26. [CrossRef] [Google Scholar]
- A.S. Mahapatra, B. Sarkar, M.S. Mahapatra, H.N. Soni and S.K. Mazumder, Development of a fuzzy economic order quantity model of deteriorating items with promotional effort and learning in fuzziness with a finite time horizon. Inventions 4 (2019) 36. [Google Scholar]
- A.S. Mahapatra, M.S. Mahapatra, B. Sarkar and S.K. Majumder, Benefit of preservation technology with promotion and time-dependent deterioration under fuzzy learning. Expert Syst. Appl. 201 (2022) 117169. [CrossRef] [Google Scholar]
- G.C. Mahata and A. Goswami, Fuzzy inventory models for items with imperfect quality and shortage backordering under crisp and fuzzy decision variables. Comput. Ind. Eng. 64 (2013) 190–199. [Google Scholar]
- U. Mishra, L.E. Cárdenas-Barrón, S. Tiwari, A.A. Shaikh and G. Treviño-Garza, An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment. Ann. Oper. Res. 254 (2017) 165–190. [Google Scholar]
- I. Moon, W.Y. Yun and B. Sarkar, Effects of variable setup cost, reliability, and production costs under controlled carbon emissions in a reliable production system. Eur. J. Ind. Eng. 16 (2022) 371–397. [CrossRef] [Google Scholar]
- M. Nouri, S.M. Hosseini-Motlagh and M. Nematollahi, Proposing a discount policy for two-level supply chain coordination with periodic review replenishment and promotional efforts decisions. Oper. Res. 21 (2021) 365–398. [Google Scholar]
- B. Oryani, A. Moridian, B. Sarkar, S. Rezania, H. Kamyab and M.K. Khan, Assessing the financial resoure curse hypothesis in Iran: The novel dynamic ARDL approach. Resour. Pol. 78 (2022) 102899. [CrossRef] [Google Scholar]
- L.Y. Ouyang, C.T. Chang and J.T. Teng, An EOQ model for deteriorating items under trade credits. J. Oper. Res. Soc. 56 (2005) 719–726. [CrossRef] [Google Scholar]
- B. Pal, Optimal pricing and offering reward decisions in a competitive closed-loop dual-channel supply chain with recycling and remanufacturing. RAIRO: OR 56 (2022) 1763–1780. [CrossRef] [EDP Sciences] [Google Scholar]
- M. Pervin, S.K. Roy and G.W. Weber, An integrated inventory model with variable holding cost under two levels of trade-credit policy. Numer. Algebra, Control Optim. 8 (2018) 169. [CrossRef] [MathSciNet] [Google Scholar]
- M. Pervin, S.K. Roy and G.W. Weber, Multi-item deteriorating two-echelon inventory model with price-and stock-dependent demand: A trade-credit policy. J. Ind. Manag. Optim. 15 (2019) 1345. [MathSciNet] [Google Scholar]
- M. Pervin, S.K. Roy and G.W. Weber, Deteriorating inventory with preservation technology under price and stock-sensitive demand. J. Ind. Manag. Optim. 16 (2020) 1585. [CrossRef] [MathSciNet] [Google Scholar]
- M. Pervin, S.K. Roy and G.W. Weber, An integrated vendor-buyer model with quadratic demand under inspection policy and preservation technology. Hacet. J. Math. Stat. 49 (2020) 1168–1189. [MathSciNet] [Google Scholar]
- P. Priyamvada, R. Rini, A. Khanna and C.K. Jaggi, An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment: revisited. Opsearch 58 (2021) 181–202. [CrossRef] [MathSciNet] [Google Scholar]
- P. Priyamvada, R. Rini and C.K. Jaggi, Optimal inventory strategies for deteriorating items with price-sensitive investment in preservation technology. RAIRO: OR 56 (2022) 601–617. [CrossRef] [EDP Sciences] [Google Scholar]
- S.K. Roy, M. Pervin and G.W. Weber, A two-warehouse probabilistic model with price discount on backorders under two levels of trade-credit policy. J. Ind. Manag. Optim. 16 (2020) 553. [CrossRef] [MathSciNet] [Google Scholar]
- S.K. Roy, M. Pervin and G.W. Weber, Imperfection with inspection policy and variable demand under trade-credit: A deteriorating inventory model. Numer. Algebra, Control Optim. 10 (2020) 45. [CrossRef] [MathSciNet] [Google Scholar]
- S. Saha, I.E. Nielsen and I. Moon, Strategic inventory and pricing decision for substitutable products. Comput. Ind. Eng. 160 (2021) 107570. [CrossRef] [Google Scholar]
- M.K. Salameh, N.E. Abboud, A.N. El-Kassar and R.E. Ghattas, Continuous review inventory model with delay in payments. Int. J. Prod. Econ. 85 (2003) 91–95. [Google Scholar]
- B. Sarkar, B.K. Dey, M. Sarkar and S.J. Kim, A smart production system with an autonomation technology and dual channel retailing, Comp. Indust. Eng. 173 (2022) 108607. [CrossRef] [Google Scholar]
- B. Sarkar, B. Ganguly, S. Pareek and L.E. Cárdenas-Barrón, A three-echelon green supply chain management for biodegradable products with three transportation modes. Comp. Ind. Eng. 174 (2022) 108727. [CrossRef] [Google Scholar]
- A. Sarkar, R. Guchhait and B. Sarkar, Application of the artificial neural network with multithreading within an inventory model under uncertainty and inflation. Int. J. Fuzzy Syst. 24 (2022) 1–15. [Google Scholar]
- B. Sarkar, J. Joo, Y. Kim, H. Park and M. Sarkar, Controlling defective items in a complex multi-phase manufacturing system. RAIRO: OR 56 (2022). [Google Scholar]
- B. Sarkar, S. Kar, K. Basu and R. Guchhait, A sustainable managerial decision-making problem for a substitutable product in a dual-channel under carbon tax policy. Comp. Ind. Eng. 172 (2022) 108635. [CrossRef] [Google Scholar]
- N.H. Shah and H.N. Soni, Continuous review inventory model with fuzzy stochastic demand and variable lead time. Int. J. Appl. Ind. Eng. 1 (2012) 7–24. [Google Scholar]
- N. Shah and M. Patel, Reducing the deterioration rate of inventory through preservation technology investment under fuzzy and cloud fuzzy environment. in Predictive Analytics, Edited by V. Kumar and M. Ram. CRC Press, Boca Raton (2021) 65–80. [CrossRef] [Google Scholar]
- N. Shah, E. Patel and K. Rabari, EPQ model to price-sensitive stock dependent demand with carbon emission under green and preservation technology investment. Econ. Comput. Econ. Cybern. Stud. Res. 56 (2022). [Google Scholar]
- N.H. Shah, K. Rabari and E. Patel, Inventory and preservation investment for deteriorating system with stock-dependent demand and partial backlogged shortages. Yugosl. J. Oper. Res. 31 (2021) 181–192. [CrossRef] [MathSciNet] [Google Scholar]
- N.H. Shah, K. Rabari and E. Patel, Greening efforts and deteriorating inventory policies for price-sensitive stock-dependent demand, Int. J. Syst. Sci.: Oper. Logist. (2022) 1–7. [Google Scholar]
- A.A. Shaikh, G.C. Panda, S. Sahu and A.K. Das, Economic order quantity model for deteriorating item with preservation technology in time dependent demand with partial backlogging and trade credit. Int. J. Logist. Syst. Manag. 32 (2019) 1. [Google Scholar]
- S.K. Sharma and S.M. Govindaluri, An analytical approach for EOQ determination using trapezoidal fuzzy function. Int. J. Procure. Manag. 11 (2018) 356–369. [Google Scholar]
- H.N. Soni and K.A. Patel, Joint pricing and replenishment policies for non-instantaneous deteriorating items with imprecise deterioration free time. Comput. Ind. Eng. 66 (2013) 944–951. [CrossRef] [Google Scholar]
- H.N. Soni and D.N. Suthar, Pricing and inventory decisions for non-instantaneous deteriorating items with price and promotional effort stochastic demand. J. Control. Decis. 6 (2019) 191–215. [CrossRef] [MathSciNet] [Google Scholar]
- R. Sundara Rajan and R. Uthayakumar, Analysis and optimization of an EOQ inventory model with promotional efforts and back ordering under delay in payments. J. Manag. Anal. 4 (2017) 159–181. [Google Scholar]
- A.A. Taleizadeh, D.W. Pentico, M.S. Jabalameli and M. Aryanezhad, An EOQ model with partial delayed payment and partial backordering. Omega 41 (2013) 354–368. [Google Scholar]
- H.M. Wee, M.C. Lee, J.C. Yu and C.E. Wang, Optimal replenishment policy for a deteriorating green product: Life cycle costing analysis. Int. J. Prod. Econ. 133 (2011) 603–611. [CrossRef] [Google Scholar]
- D. Yadav, R. Singh, A. Kumar and B. Sarkar, Reduction of pollution through sustainable and flexible production by controlling by-products. J. Environ. Inf. 40 (2022) 106–124. [Google Scholar]
- J.S. Yao, S.C. Chang and J.S. Su, Fuzzy inventory without backorder for fuzzy order quantity and fuzzy total demand quantity. Comput. Oper. Res. 27 (2000) 935–962. [Google Scholar]
- L.A. Zadeh, Fuzzy sets. Inf. Control 8 (1965) 338–353. [Google Scholar]
- J. Zhang, Y. Wang, L. Lu and W. Tang, Optimal dynamic pricing and replenishment cycle for non-instantaneous deterioration items with inventory-level-dependent demand. Int. J. Prod. Econ. 170 (2015) 136–145. [Google Scholar]
- Q. Zhou, Y. Yang and S. Fu, Deep reinforcement learning approach for solving joint pricing and inventory problem with reference price effects. Expert Syst. Appl. 195 (2022) 116564. [CrossRef] [Google Scholar]
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