Open Access
RAIRO-Oper. Res.
Volume 56, Number 2, March-April 2022
Page(s) 871 - 889
Published online 14 April 2022
  • W. Ahmed, M. Moazzam, B. Sarkar and S.U. Rehman, Synergic effect of reworking for imperfect quality items with the integration of multi-period delay-in-payment and partial backordering in global supply chains. Engineering 7 (2021) 260–271. [CrossRef] [MathSciNet] [Google Scholar]
  • H.K. Alfares and A.M. Ghaithan, Inventory and pricing model with price-dependent demand, time-varying holding cost, and quantity discounts. Comp. Ind. Engin. 94 (2016) 170–177. [CrossRef] [Google Scholar]
  • K. Biel and C.H. Glock, Governing the dynamics of multi-stage production systems subject to learning and forgetting effects: a simulation study. Int. J. Prod. Res. 56 (2018) 3439–3461. [CrossRef] [Google Scholar]
  • S. Bhuniya, S. Pareek and B. Sarkar, A supply chain model with service level constraints and strategies under uncertainty. Alex. Engin. J. 60 (2021) 6035–6052. [CrossRef] [Google Scholar]
  • B.K. Dey, B. Sarkar, M. Sarkar and S. Pareek, An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment. RAIRO-Oper. Res. 53 (2019) 39–57. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • B.K. Dey, S. Bhuniya and B. Sarkar, Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Exp. Sys. Appl. 184 (2021) 115464. [CrossRef] [Google Scholar]
  • B.K. Dey, S. Pareek, M. Tayyab and B. Sarkar, Autonomation policy to control work-in-process inventory in a smart production system. Int. J. Prod. Res. 59 (2021) 1258–1280. [Google Scholar]
  • O. Dowson, A. Philpott, A. Mason and A. Downward, A multi-stage stochastic optimization model of a pastoral dairy farm. Euro. J. Oper. Res. 274 (2019) 1077–1089. [CrossRef] [Google Scholar]
  • K. Forghani, A. Mirzazadeh and M. Rafiee, A price-dependent demand model in the single period inventory system with price adjustment. J. Ind. Eng. (2013)1–9. [Google Scholar]
  • B.B. Gardas, R.D. Raut and B. Narkhede, Evaluating critical causal factors for post-harvest losses (PHL) in the fruit and vegetables supply chain in India using the DEMATEL approach. J. Clean. Prod. 199 (2018) 47–61. [CrossRef] [Google Scholar]
  • J.P. Gayon, S. Vercraene and S.D.P. Flapper, Optimal control of a production-inventory system with product returns and two disposal options. Euro. J. Oper. Res. 262 (2017) 499–508. [CrossRef] [Google Scholar]
  • C.H. Glock and M.Y. Jaber, A multi-stage production-inventory model with learning and forgetting effects, rework and scrap. Comp. Ind. Engin. 64 (2013) 708–720. [CrossRef] [Google Scholar]
  • M. Golari, N. Fan and T. Jin, Multistage stochastic optimization for production-inventory planning with intermittent renewable energy. Prod. Oper. Manag. 26 (2017) 409–425. [CrossRef] [Google Scholar]
  • S. Gupta, A. Haq, I. Ali and B. Sarkar, Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment. Compl. Intell. Syst. 7 (2021) 2119–2139. [CrossRef] [Google Scholar]
  • R. Hammad, I.U. Khan, S. Asghar, S.H. Khalid, M. Irfan, I. Khalid, S.U. Shah, N. Sabir, A. Ali, A.M. Yousaf, T. Hussain, Y. Shahzad and U.F. Gohar, Multi-stage release matrices for potential antiplatelet therapy: assessing the impact of polymers and Sorb-Cel M on floating, swelling, and release behaviour. J. Drug Del. Sci. Technol. 55 (2020) 101387. [CrossRef] [Google Scholar]
  • A. Garai and B. Sarkar, Economically independent reverse logistics of customer-centric closed-loop supply chain for herbal medicines and biofuel. J. Clean. Prod. 334 (2022) 129977. [CrossRef] [Google Scholar]
  • 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. [Google Scholar]
  • S. Kumar, B. Sarkar and A. Kumar, Fuzzy reverse logistics inventory model of smart items with two warehouses of a retailer considering carbon emissions. RAIRO-Oper. Res. 55 (2021) 2285–2307. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • A.S. Mahapatra, H.N. Soni, M.S. Mahapatra, B. Sarkar and S. Majumder, A continuous review production-inventory system with a variable preparation time in a fuzzy random environment. Mathematics 9 (2021) 747. [CrossRef] [Google Scholar]
  • L. Makarichi, W. Jutidamrongphan and K. Techato, The evolution of waste-to-energy incineration: A review. Renew. Sustain. Ener. Rev. 91 (2018) 812–822. [CrossRef] [Google Scholar]
  • A.H.M. Mashud and B. Sarkar, Retailer’s joint pricing model through an effective preservation strategy under a trade-credit policy. RAIRO-Oper. Res. 55 (2021) 1799–1823. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • L. Meherishi, S.A. Narayana and K.S. Ranjani, Integrated product and packaging decisions with secondary packaging returns and protective packaging management. Euro. J. Oper. Res. 292 (2021) 930–952. [CrossRef] [Google Scholar]
  • M. Omair, S. Noor, M. Tayyab, S. Maqsood, W. Ahmed, B. Sarkar and, M.S. Habib, The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. Int. J. Fuz. Sys. 23 (2021) 1986–2003. [CrossRef] [Google Scholar]
  • S. Saha, I. Nielsen and I. Moon, Optimal retailer investments in green operations and preservation technology for deteriorating items. J. Clean. Prod. 140 (2017) 1514–1527. [Google Scholar]
  • S.K. Sardar, B. Sarkar and B. Kim, Integrating machine learning, radio frequency identification, and consignment policy for reducing unreliability in smart supply chain management. Processes 9 (2021) 247. [CrossRef] [Google Scholar]
  • B. Sarkar, Mathematical and analytical approach for the management of defective items in a multi-stage production system. J. Clean. Prod. 218 (2019) 896–919. [CrossRef] [Google Scholar]
  • B. Sarkar, M. Ullah and M. Sarkar, Environmental and economic sustainability through innovative green products by remanufacturing. J. Clean. Prod. 332 (2022) 129813. [CrossRef] [Google Scholar]
  • M. Sarkar and B. Sarkar, How does an industry reduce waste and consumed energy within a multi-stage smart sustainable biofuel production system?. J. Clean. Prod. 262 (2020) 121200. [CrossRef] [Google Scholar]
  • S. Kumar, M. Sigroha, K. Kumar and B. Sarkar, Manufacturing/remanufacturing based supply chain management under advertisements and carbon emission process. RAIRO-Oper. Res. (2022). [Google Scholar]
  • B.R. Sarker, A.M.M. Jamal and S. Mondal, Optimal batch sizing in a multi-stage production system with rework consideration. Euro. J. Oper. Res. 184 (2008) 915–929. [CrossRef] [Google Scholar]
  • N. Saxena, B. Sarkar and S.R. Singh, Selection of remanufacturing/production cycles with an alternative market: a perspective on waste management. J. Clean. Prod. 245 (2020) 118935. [CrossRef] [Google Scholar]
  • A. Sepehri, U. Mishra, M.L. Tseng and B. Sarkar, Joint pricing and inventory model for deteriorating items with maximum lifetime and controllable carbon emissions under permissible delay in payments. Mathematics 9 (2021) 470. [CrossRef] [Google Scholar]
  • A.A. Shaikh, S.C. Das, A.K. Bhunia and B. Sarkar, Decision support system for customers during availability of trade credit financing with different pricing situations. RAIRO-Oper. Res. 55 (2021) 1043. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • S.R. Vandana, D. Singh, B.Sarkar Yadav and M. Sarkar, Impact of energy and carbon emission of a supply chain management with two-level trade-credit policy. Energies 14 (2021) 1569. [CrossRef] [Google Scholar]
  • G. Sołowski, I. Konkol and A. Cenian, Production of hydrogen and methane from lignocellulose waste by fermentation. A review of chemical pretreatment for enhancing the efficiency of the digestion process. J. Clean. Prod. 267 (2020) 121721. [CrossRef] [Google Scholar]
  • 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. [CrossRef] [Google Scholar]
  • M. Tayyab and B. Sarkar, An interactive fuzzy programming approach for a sustainable supplier selection under textile supply chain management. Comp. Ind. Eng. 155 (2021) 10716. [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. Indust. Eng (2022). [Google Scholar]
  • M. Ullah and B. Sarkar, Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality. Int. J. Prod. Econ. 219 (2020) 360–374. [Google Scholar]
  • M. Ullah, I. Asghar, M. Zahid, M. Omair, A. Alarjani and B. Sarkar, Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. J. Clean. Prod. 290 (2021) 125609. [CrossRef] [Google Scholar]
  • C. Weller, R. Kleer and F.T. Piller, Economic implications of 3D printing: market structure models in light of additive manufacturing revisited. Int. J. Prod. Econ. 164 (2015) 43–56. [CrossRef] [Google Scholar]
  • D. Yadav, R. Kumari, N. Kumar and B. Sarkar, Reduction of waste and carbon emission through the selection of items with cross-price elasticity of demand to form a sustainable supply chain with preservation technology. J. Clean. Prod. 297 (2021) 126298. [CrossRef] [Google Scholar]

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