An environmental decision support system for manufacturer-retailer within a closed-loop supply chain management using remanufacturing

i

This article has been updated. A Correction to this article was published on .

i

The Original Article was published on

i

The Original Article was published on

i

This article has been updated

i

This article was retracted on

i

This article has been updated

Abstract

Industries face many challenges when emergencies arise. In emergency, there is an increasing demand for self-administered products that are easy to use. The decay rate of these products decreases with time. Moreover, the lack of disposal of used products increases waste and carbon emissions. By observing the scenario, this study develops a closed-loop supply chain management that considers the collection and remanufacturing of used products. The manufacturing rate is linear and the demand is ramp-type and carbon emissions dependent. The model is solved by a classical optimization and calculates the optimal total cost. The results show that the retailer can handle a shortage situation when the demand becomes stable (Case 2) and the total cost increases with the production rate. A sensitivity analysis shows the changes in the total cost with respect to the parameters.

Keywords

supply chain management / cost and cost analysis / decision making / reverse logistics / emission reduction

CHANGE HISTORY

A Correction to this paper has been published:
https://doi.org

The Retraction Note was updated to reflect reception of statements of disagreement from all authors.

This article has been retracted.Please see the Retraction Notice for more detail:
https://doi.org

References

[1] Rani S, Ali R, Agarwal A (2022) Fuzzy inventory model for new and refurbished deteriorating items with cannibalisation in green supply chain. Int J Syst Sci Operat Logist 9: 22-38. https://doi.org/10.1080/23302674.2020.1803434

[2] Sarkar B, Sarkar M, Ganguly B, et al. (2020) Combined effects of carbon emission and production quality improvement for fixed lifetime products in a sustainable supply chain management. Int J Prod Econ 231: 107867. https://doi.org/10.1016/j.ijpe.2020.107867

[3] Sarkar B, Guchhait R (2023) Ramification of information asymmetry on a green supply chain management with the cap-trade, service, and vendor-managed inventory strategies. Elect Commer Res App 60: 101274. https://doi.org/10.1016/j.elerap.2023.101274

[4] Saxena N, Sarkar B, Wee H M, et al. (2023) A reverse logistics model with eco-design under the Stackelberg-Nash equilibrium and centralized framework. J Clean Prod 387: 135789. https://doi.org/10.1016/j.jclepro.2022.135789

[5] Ullah M, Asghar I, Zahid M, et al. (2021) Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. J Clean Prod 290: 125609. https://doi.org/10.1016/j.jclepro.2020.125609

[6] Sarkar B, Bhuniya S (2022) A sustainable flexible manufacturing-remanufacturing model with improved service and green investment under variable demand, Exp Syst with Appli 202: 117154. https://doi.org/10.1016/j.eswa.2022.117154

[7] Cheng S, Zhang F, Chen X (2024) Optimal contract design for a supply chain with information asymmetry under dual environmental responsibility constraints. Exp Syst App 237: 121466. https://doi.org/10.1016/j.eswa.2023.121466

[8] Kumar S, Kumar A, Jain M (2020) Learning effect on an optimal policy for mathematical inventory model for decaying items under preservation technology with the environment of COVID-19 pandemic. Malaya J Matemat 8: 1694-1702. https://doi.org/10.26637/MJM0804/0063

[9] Dey B K, Bhuniya S, Sarkar B (2021) Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Exp Syst App 184: 115464. https://doi.org/10.1016/j.eswa.2021.115464

[10] Ullah M, Sarkar B (2020) Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality. Int J Prod Econ 219: 360-374. https://doi.org/10.1016/j.ijpe.2019.07.017

[11] Cheng M, Zhang B, Wang G (2011) Optimal policy for deteriorating items with trapezoidal type demand and partial backlogging. App Math Model 35: 3552-3560. https://doi.org/10.1016/j.apm.2011.01.001

[12] Rini, Priyamvada, Jaggi C K (2021) Sustainable and flexible production system for a deteriorating item with quality consideration. Int J Syst Assuran Eng Manag 12: 951-960. https://doi.org/10.1007/s13198-021-01169-w

[13] Kawakatsu H (2010) Optimal retailer's replenishment policy for seasonal products with ramp-type demand rate. Int J App Math 40: 1-7.

[14] Panda S, Senapati S, Basu M (2008) Optimal replenishment policy for perishable seasonal products in a season with ramp-type time dependent demand. Comput Indust Eng 54: 301-314. https://doi.org/10.1016/j.cie.2007.07.011

[15] Sarkar B, Ullah M, Sarkar M (2022) Environmental and economic sustainability through innovative green products by remanufacturing. J Clean Prod 332: 129813. https://doi.org/10.1016/j.jclepro.2021.129813

[16] Saha S, Sarkar B, Sarkar M (2023) Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies. Math Comp Simul 209: 426-450. https://doi.org/10.1016/j.matcom.2023.02.005

[17] Skouri K, Konstantaras I, Papachristos S, et al. (2009) Inventory models with ramp type demand rate, partial backlogging and Weibull deterioration rate. Euro J Operat Res 192: 79-92. ttps://doi.org/ 10.1016/j.ejor.2007.09.003

[18] Wu J, Skouri K, Teng J T, et al. (2016) Two inventory systems with trapezoidal-type demand rate and time-dependent deterioration and backlogging. Exp Syst App 46: 367-379. https://doi.org/10.1016/j.eswa.2015.10.048

[19] Wee H M, Chung c C J (2009) Optimizing replenishment policy for an integrated production inventory deteriorating model considering green component-value design and remanufacturing. Int J Prod Res 47: 1343-1368. https://doi.org/10.1080/00207540701570182

[20] Miramontes-Viña V, Romero-Castro N, López-Cabarcos M Á (2023) Advancing towards a sustainable energy model. Uncovering the untapped potential of rural areas. AIMS Env Sci 10: 287-312. https://doi.org/10.3934/environsci.2023017

[21] Monteiro S, Amor-Esteban V, Lemos K, et al. (2023) Are we doing the same? A worldwide analysis of business commitment to the SDGs. AIMS Env Sci 10: 446-466. https://doi.org/10.3934/environsci.2023025

[22] Osabuohien-Irabor O, Drapkin I M (2023) Toward achieving zero-emissions in European Union countries: The contributions of trade and overseas direct investments in consumptionbased carbon emissions. AIMS Env Sci 10: 129-156. https://doi.org/10.3934/environsci.2023008

[23] Zhou X, Zhu Q, Xu L, et al. (2024) The effect of carbon tariffs and the associated coping strategies: A global supply chain perspective. Omega 122: 102960. https://doi.org/10.1016/j.omega.2023.102960

[24] Rossit D, Guggeri E M, Ham C, et al. (2023) Goal programming and multi-criteria methods in remanufacturing and reverse logistics: Systematic literature review and survey. Comp Indust Eng 109587. https://doi.org/10.1016/j.cie.2023.109587

[25] Jaber M Y, El Saadany A M A (2009) The production, remanufacture and waste disposal model with lost sales. Int J Prod Econ 115-124. https://doi.org/10.1016/j.ijpe.2008.07.016

[26] Konstantaras I, Skouri K, Jaber M Y (2010) Lot sizing for a recoverable product with inspection and sorting, Comput Indust Eng 58: 452-462. https://doi.org/10.1016/j.cie.2009.11.004

[27] Koh S G, Hwang H, Sohn K I, et al. (2002) An optimal ordering and recovery policy for reusable items. Comput Indust Eng 43: 59-73. https://doi.org/10.1016/S0360-8352(02)00062-1

[28] Liao T Y (2018) Reverse logistics network design for product recovery and remanufacturing. App Math Model 60: 145-163. https://doi.org/10.1016/j.apm.2018.03.003

[29] Marić J, Opazo-Basáez M (2019) Green servitization for flexible and sustainable supply chain operations: A review of reverse logistics services in manufacturing. Global J Flex Syst Manag 20: S65-S80. https://doi.org/10.1007/s40171-019-00225-6

[30] Weng Z K, McClurg T (2003) Coordinated ordering decisions for short life cycle products with uncertainty in delivery time and demand. Euro J Operat Res 151: 12-24. https://doi.org/10.1016/S0377-2217(02)00577-5

[31] Ahmadi S, Shokouhyar S, Amerioun M, et al. (2024) A social media analytics-based approach to customer-centric reverse logistics management of electronic devices: A case study on notebooks. J Retail Consum Serv 76: 103540. https://doi.org/10.1016/j.jretconser.2023.103540

[32] Ahmed W, Sarkar B (2019) Management of next-generation energy using a triple bottom line approach under a supply chain framework. Resour Conserv Recyc 150: 104431. https://doi.org/10.1016/j.resconrec.2019.104431

[33] Goodarzian F, Ghasemi P, Gonzalez E D R S, et al. (2023) A sustainable-circular citrus closed-loop supply chain configuration: Pareto-based algorithms. J Environ Manag 328: 116892. https://doi.org/10.1016/j.jenvman.2022.116892

[34] Momenitabar M, Dehdari Ebrahimi Z, Arani M, et al. (2022) Designing a sustainable closed-loop supply chain network considering lateral resupply and backup suppliers using fuzzy inference system. Environ Dev Sustain https://doi.org/10.1007/s10668-022-02332-4.

[35] Mashud A H M, Pervin M, Mishra U, et al. (2021) A sustainable inventory model with controllable carbon emissions in green-warehouse farms. J Clean Prod 298: 126777. https://doi.org/10.1016/j.jclepro.2021.126777

[36] Sarkar B, Omair M, Kim N (2020) A cooperative advertising collaboration policy in supply chain management under uncertain conditions. App Soft Comput 88: 105948. https://doi.org/10.1016/j.asoc.2019.105948

[37] Mishra U, Wu J Z, Sarkar B (2021) Optimum sustainable inventory management with backorder and deterioration under controllable carbon emissions. J Clean Prod 279: 123699. https://doi.org/10.1016/j.jclepro.2020.123699

[38] Kugele A S H, Sarkar B (2023) Reducing carbon emissions of a multi-stage smart production for biofuel towards sustainable development. Alex Eng J 70: 93-113. https://doi.org/10.1016/j.aej.2023.01.003

[39] Mridha B, Pareek S, Goswami A, et al. (2023) Joint effects of production quality improvement of biofuel and carbon emissions towards a smart sustainable supply chain management. J Clean Prod 386: 135629. https://doi.org/10.1016/j.jclepro.2022.135629

[40] Teng Y, Feng B (2021) Optimal channel structure for remanufacturing under cap-and-trade regulation. Process 9: 370. https://doi.org/10.3390/pr9020370

[41] Tiwari S, Daryanto Y, Wee H M (2018) Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. J Clean Prod 192: 281-292. https://doi.org/10.1016/j.jclepro.2018.04.261

[42] Yadav S, Khanna A (2021) Sustainable inventory model for perishable products with expiration date and price reliant demand under carbon tax policy. Proces Int Opt Sust 5: 475-486. https://doi.org/10.1007/s41660-021-00157-8

[43] Mishra U, Wu J Z, Sarkar B (2020) A sustainable production-inventory model for a controllable carbon emissions rate under shortages. J Clean Prod 256: 120268. https://doi.org/10.1016/j.jclepro.2020.120268

[44] Babaeinesami A, Tohidi H, Ghasemi P, et al. (2022) A closed-loop supply chain configuration considering environmental impacts: A self-adaptive NSGA-II algorithm. App Intell 52: 13478-13496. https://doi.org/10.1007/s10489-021-02944-9

[45] Goodarzian F, Kumar V, Ghasemi P (2022) Investigating a citrus fruit supply chain network considering CO₂ emissions using meta-heuristic algorithms . Ann Oper Res https://doi.org/10.1007/s10479-022-05005-7.

[46] Alamri A A (2010) Theory and methodology on the global optimal solution to a general reverse logistics inventory model for deteriorating items and time-varying rates. Comput Indust Eng 60: 236-247. https://doi.org/10.1016/j.cie.2010.11.005

[47] Chung C J, Wee H M Short (2011) lifecycle deteriorating product remanufacturing in a green supply chain inventory control system. Int J Prod Econ 129: 195-203. https://doi.org/10.1016/j.ijpe.2010.09.033

[48] Motla R, Kumar A, Singh S R, et al. (2021) A fuzzy integrated inventory system with end of life treatment: A possibility in sport industry. Opsearch 58: 869-888. https://doi.org/10.1007/s12597-020-00492-3

[49] Rani S, Ali R, Agarwal A (2019) Fuzzy inventory model for deteriorating items in a green supply chain with carbon concerned demand. Opsearch 56: 91-122. https://doi.org/10.1007/s12597-019-00361-8

[50] Rani S, Ali R, Agarwal A (2020) Inventory model for deteriorating items in green supply chain with credit period dependent demand. Int J App Eng Res 15: 157-172.

[51] Garai A, Sarkar B (2022) Economically independent reverse logistics of customer-centric closed-loop supply chain for herbal medicines and biofuel J Clean Prod 334: 129977. https://doi.org/10.1016/j.jclepro.2021.129977

[52] Safdar N, Khalid R, Ahmed W, et al. (2020) Reverse logistics network design of e-waste management under the triple bottom line approach. J Clean Prod 272: 122662. https://doi.org/10.1016/j.jclepro.2020.122662

[53] Sarkar B, Debnath A, Chiu A S F, et al. (2022) Circular economy-driven two-stage supply chain management for nullifying waste. J Clean Prod 339: 130513. https://doi.org/10.1016/j.jclepro.2022.130513

[54] Singh S R, Sharma S (2019) A partially backlogged supply chain model for deteriorating items under reverse logistics, imperfect production/remanufacturing and inflation. Int J Logist Syst Manag 33: 221. https://doi.org/10.1504/IJLSM.2019.100113

[55] Wang C, Huang R (2014) Pricing for seasonal deteriorating products with price-and ramp-type time-dependent demand. Comput Indust Eng 77: 29-34. https://doi.org/10.1016/j.cie.2014.09.005

[56] Yang P C, Chung S L, Wee H M, et al. (2013) Collaboration for a closed-loop deteriorating inventory supply chain with multi-retailer and price-sensitive demand. Int J Prod Econ 143: 557-566. https://doi.org/10.1016/j.ijpe.2012.07.020

[57] Sarkar M, Sarkar B (2020) How does an industry reduce waste and consumed energy within a multi-stage smart sustainable biofuel production system? J Clean Prod 262: 121200. https://doi.org/10.1016/j.jclepro.2020.121200

[58] Dey B K, Pareek S, Tayyab M, et al. (2021) Autonomation policy to control work-in-process inventory in a smart production system. Int J Prod Res 59: 1258-1280. https://doi.org/10.1080/00207543.2020.1722325

[59] Li P, Chen B, Cui Q (2023) A probabilistic life-cycle assessment of carbon emission from magnesium phosphate cementitious material with uncertainty analysis. J Clean Prod 139164. https://doi.org/10.1016/j.jclepro.2023.139164

[60] Habib M S, Asghar O, Hussain A, et al. (2021) A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment. J Clean Prod 278: 122403. https://doi.org/10.1016/j.jclepro.2020.122403

[61] Sarkar B, Tayyab M, Kim N, et al. (2019) Optimal production delivery policies for supplier and manufacturer in a constrained closed-loop supply chain for returnable transport packaging through metaheuristic approach. Comp Indust Eng 135: 987-1003. https://doi.org/10.1016/j.cie.2019.05.035

[62] Singh S K, Chauhan A, Sarkar B (2023) Sustainable biodiesel supply chain model based on waste animal fat with subsidy and advertisement. J Clean Prod 382: 134806. https://doi.org/10.1016/j.jclepro.2022.134806

[63] Ke C, Pan X, Wan P, et al. (2023) An integrated design method for used product remanufacturing scheme considering carbon emission. Sustain Prod Consum 41: 348-361. https://doi.org/10.1016/j.spc.2023.08.018

[64] Huang J, Yan Y, Kang J, et al. (2023) Driving technology factors of carbon emissions: Theoretical framework and its policy implications for China. Sci Total Environ 904: 166858. https://doi.org/10.1016/j.scitotenv.2023.166858

[65] Tiwari S, Ahmed W, Sarkar B (2019) Sustainable ordering policies for non-instantaneous deteriorating items under carbon emission and multi-trade-credit-policies. J Clean Prod 240: 118183. https://doi.org/10.1016/j.jclepro.2019.118183

[66] Sepehri A, Mishra U, Sarkar B (2021) A sustainable production-inventory model with imperfect quality under preservation technology and quality improvement investment. J Clean Prod 310: 127332. https://doi.org/10.1016/j.jclepro.2021.127332

[67] Yadav D, Kumari R, Kumar N, et al. (2021) 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: 126298. https://doi.org/10.1016/j.jclepro.2021.126298

[68] Tayyab M, Jemai J, Lim H, et al. (2020) A sustainable development framework for a cleaner multi-item multi-stage textile production system with a process improvement initiative. J Clean Prod 246: 119055. https://doi.org/10.1016/j.jclepro.2019.119055

[69] Mao H, Wang W, Liu C, et al. (2023) Effects of the carbon emission quota policy on the quality and sales of manufactured and remanufactured products. Int J Prod Econ 266: 109058. https://doi.org/10.1016/j.ijpe.2023.109058

[70] LI Y, YI F, YUAN C Influences of large-scale farming on carbon emissions from cropping: Evidence from China. J Integr Agricul https://doi.org/10.1016/j.jia.2023.08.006