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Farklı karbon emisyon politikaları altında sağlam bir kapalı döngü tedarik zinciri şebeke tasarımı

Yıl 2019, Cilt: 25 Sayı: 9, 1020 - 1032, 31.12.2019

Öz

Son zamanlarda, kapalı bir döngü tedarik zinciri ağı tasarlama konusu araştırmacının dikkatini çekti. Bu, kapalı döngü tedarik zinciri uygulamalarından elde edilen çok büyük finansal ve çevresel faydalardan kaynaklanmaktadır. Bu makale, dört karbon emisyonu düzenleme politikası kapsamında aşağı yönlü ürün ikame politikasını dikkate alan kapalı döngü tedarik zinciri ağı tasarlama modeline değinmektedir: karbon sınırı politikası, karbon vergisi politikası, karbon sınırı ve ticaret politikası ve karbon dengesi politikası Ürün talebindeki varsayılan belirsizlikleri ve iade edilen ürün sayısını çözmek için, sağlam optimizasyon benimsendi. Önerilen modelin amacı, hangi tesisin açılacağını / işletileceğini seçmek, bir nakliye modu seçmek ve sevk edilen ve ikame edilen ürünlerin miktarını belirlemektir. Dört karbon emisyonu düzenleme politikasını kullanmaya ilişkin sayısal bir örnek gösteriyoruz.

Kaynakça

  • Ilgin MA, Gupta SM. Reverse Logistics. Editor: Gupta SM Reverse Supply Chains: Issues and Analysis, 1-60, Boca Raton, FL, USA, CRC Press, 2013.
  • Mohammed F, Selim SZ, Hassan A, Syed MN, “Multi-period planning of closed-loop supply chain with carbon policies under uncertainty”. Transportation Research Part D Transport and Environment, 51, 146-172, 2017.
  • Diabat A, Abdallah T, Al-refaie A,. Svetinovic D, Govindan K. “Strategic Closed-Loop Facility Location Problem”. IEEE Transactions on Engineering Management, 60(2), 398-408, 2013.
  • Jin M, Granda-Marulanda NA, Down I. “The impact of carbon policies on supply chain design and logistics of a major retailer”. Journal of Cleaner Prodoction, 85, 453-461, 2014.
  • Benjaafar S, Li Y, Daskin M. “Carbon footprint and the management of supply chains: Insights from simple models”. IEEE Transactions on Automation Science and Engineering, 10(1), 99-116, 2013.
  • Mohajeri A, Fallah M. “A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study”. Transportation Research Part D Transport and Environment, 48, 425-450, 2016.
  • He L, Hu C, Zhao D, Lu H, Fu X, Li Y. “Carbon emission mitigation through regulatory policies and operations adaptation in supply chains: theoretic developments and extensions”. Natural Hazards, 84(1), 179-207, 2016.
  • Fareeduddin M, Hassan A, Syed MN, Selim SZ. “The impact of carbon policies on closed-loop supply chain network design”. Procedia CIRP, 26, 335-340, 2015.
  • Gungor A, Gupta SM. “Issues in environmentally conscious manufacturing and product recovery: A survey”. Computers & Industrial Engineering, 36(4), 811-853, 1999.
  • Ilgin MA, Gupta SM. “Environmentally conscious manufacturing and product recovery ( ECMPRO ): A review of the state of the art”. Journal of Environmental Management, 91(3), 563-591, 2010.
  • Wei J, Zhao J. “Reverse channel decisions for a fuzzy closed-loop supply chain”. Applied Mathematical Modelling, 37(3), 1502-1513, 2013.
  • Hong IH, Yeh JS. “Modeling closed-loop supply chains in the electronics industry: A retailer collection application”. Transportation Research Part E: Logistics and Transportation Review, 48(4), 817-829, 2012.
  • Pishvaee MS, Jolai F, Razmi J. “A stochastic optimization model for integrated forward/reverse logistics network design”. Journal of Manufacturing Systems, 28(4), 107-114, 2009.
  • Pochampally KK, Nukala S, Gupta SM. Strategic planning models for reverse and closed-loop supply chains. Boca Raton, Florida: CRC Press, 2009.
  • Ferguson M. “Strategic and Tactical Aspects of Closed-Loop Supply Chains”. Foundations and Trends® in Technology, Information and Operations Management, 3(2), 101-200, 2009.
  • Jayaraman V, Guide VDR, Srivastava R. “A closed-loop logistics model for remanufacturing”. Journal of the Operational Research Society, 50(5), 497-508, 1999.
  • Beamon BM, Fernandes C. “Supply-chain network configuration for product recovery”. Production Planning & Control, 15(3), 270-281, 2004.
  • Demirel NÖ, Gökçen H. “A mixed integer programming model for remanufacturing in reverse logistics environment”. International Journal of Advanced Manufacturing Technology, 39(11-12), 1197-1206, 2008.
  • Özceylan E, Paksoy T. “A mixed integer programming model for a closed-loop supply-chain network”. International Journal of Production Research, 51(3), 718-734, 2013.
  • Kalaitzidou MA, Longinidis P, Georgiadis MC. “Optimal design of closed-loop supply chain networks with multifunctional nodes”. Computers & Chemical Engineering, 80, 73-91, 2015.
  • Listeş O. “A generic stochastic model for supply-and-return network design”. Computers & Operations Research, 34(2), 417-442, 2007.
  • Chouinard M, D’Amours S, Aït-Kadi D. “A stochastic programming approach for designing supply loops”. International Journal of Production Economics, 113(2), 657-677, 2008.
  • Soleimani H, Govindan K. “Reverse logistics network design and planning utilizing conditional value at risk”. European Journal of Operational Research, 237(2), 487-497, 2014.
  • Qin Z, Ji X. “Logistics network design for product recovery in fuzzy environment”. European Journal of Operational Research, 202(2), 479-490, 2010.
  • Pishvaee MS, Torabi SA. “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”. Fuzzy Sets and Systems, 161(20), 2668-2683, 2010.
  • Jindal A, Sangwan KS. “Closed loop supply chain network design and optimisation using fuzzy mixed integer linear programming model”. International Journal of Production Research, 52(14), 4156-4173, 2014.
  • Haddadsisakht A, Ryan SM. “Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax”. International Journal of Production Economics, 195, 118-131, 2018.
  • Ilgin MA, Gupta SM, Battaïa O. “Use of MCDM techniques in environmentally conscious manufacturing and product recovery: State of the art”. Journal of Manufacturing Systems, 37, 746-758, 2015.
  • Gupta SM, Ilgin MA. Multiple Criteria Decision Making Applications in Environmentally Conscious Manufacturing and Product Recovery. Boca Raton, Florida: CRC Press, 2018.
  • Amin SH, Zhang G. “Closed-loop supply chain network configuration by a multi-objective mathematical model”. International Journal of Business Performance and Supply Chain Modelling, 6(1), 1-15, 2014.
  • Shi J, Liu Z, Tang L, Xiong J. “Multi-objective optimization for a closed-loop network design problem using an improved genetic algorithm”. Applied Mathematical Modelling, 45, 14-30, 2016.
  • Nukala S, Gupta SM. “Strategic and tactical planning of a closed-loop supply chain network under uncertainty”. SPIE International Conference on Environmentally Conscious Manufacturing VI, Boston, USA, 01-03 October 2006.
  • Amin SH, Zhang G. “A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return”. Applied Mathematical Modelling, 37(6), 4165-4176, 2013.
  • Paksoy T, Pehlivan NY, Özceylan E. “Fuzzy Multi-Objective Optimization of a Green Supply Chain Network with Risk Management that Includes Environmental Hazards”. Human and Ecological Risk Assessment: An International Journal, 18(5), 1120-1151, 2012.
  • Pishvaee MS, Rabbani M, Torabi SA. “A robust optimization approach to closed-loop supply chain network design under uncertainty”. Applied Mathematical Modelling, 35(2), 637-649, 2011.
  • Özceylan E, Paksoy T. “Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty”. International Journal of Production Research, 52(8), 2363-2387, 2014.
  • Jindal A, Sangwan KS. “Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors”. Annals of Operations Research, 257(1-2), 95-120, 2017.
  • Zhen L, Huang L, Wang W. “Green and sustainable closed-loop supply chain network design under uncertainty”. Journal of Cleaner Prodoction, 227, 1195-1209, 2019.
  • Ahiska SS, Gocer F, King RE. “Heuristic inventory policies for a hybrid manufacturing/remanufacturing system with product substitution”. Computers &. Industrial Engineering, 114, 206-222, 2017.
  • Ghafarimoghadam A, Karimi A, Mousazadeh M, Pishvaee MS. “A robust optimisation model for remanufacturing network design problem with one-way substitution”. International Journal of Services and Operations Management, 24(4), 484-503, 2016.
  • Fahimnia B, Sarkis J, Dehghanian F, Banihashemi N, Rahman S. “The impact of carbon pricing on a closed-loop supply chain: An Australian case study”. Journal of Cleaner Prodoction, 59, 210-225, 2013.
  • Mohammed F, Hassan A, Selim SZ. “Carbon market sensitive robust optimization model for closed loop supply chain network design under uncertainty”. Journal of Physics: Conference Series, 1150(1), 1-10, 2019.
  • Shin H, Park S, Lee E, Benton WC. “A classification of the literature on the planning of substitutable products”. European Journal of Operational Research, 246(3), 686-699, 2015.
  • Lang JC. “Production and inventory management with substitutions”. Lecture Notes in Economics and Mathematical Systems, 636, 1-258, 2010.
  • Bayindir ZP, Erkip N, Güllü R. “Assessing the benefits of remanufacturing option under one-way substitution”. Journal of the Operational Research Society, 56(3), 286-296, 2005.
  • Bayindir ZP, Erkip N, Güllü R. “Assessing the benefits of remanufacturing option under one-way substitution and capacity constraint”. Computers & Operations Research, 34(2), 487-514, 2007.
  • Li Y, Chen J, Cai X. “Uncapacitated production planning with multiple product types, returned product remanufacturing, and demand substitution”. OR Spectrum, 28(1), 101-125, 2006.
  • Piñeyro P, Viera O. “The economic lot-sizing problem with remanufacturing and one-way substitution,” Int. J. Prod. Econ., 156, 167-168, 2010.
  • A. Choudhary, S. Sarkar, S. Settur, and M. K. Tiwari, “A carbon market sensitive optimization model for integrated forward-reverse logistics”. International Journal of Production Economics, 164, 433-444, 2015.
  • Mulvey JM, Vanderbei RJ, Zenios SA. “Robust Optimization of Large-Scale Systems”. Operations Research, 43(2), 264-281, 1995.
  • Yu C, Li H. “A robust optimization model for stochastic logistic problems”. International Journal of Production Economics, 64(1-3), 385-397, 2000.
  • Li HL, “An efficient method for solving linear goal programming problems”. Journal of Optimization Theory and Applications, 90(2), 465-469, 1996.

A robust closed loop supply chain network design under different carbon emission policies

Yıl 2019, Cilt: 25 Sayı: 9, 1020 - 1032, 31.12.2019

Öz

Recently, the topic of designing a closed loop supply chain network has attracted researchers’ attention due to the enormous financial and environmental benefits obtained from its practices. This paper addresses a new model of designing a closed loop supply chain network, which considers a downward product substitution policy under four carbon emission regulation policies: carbon cap, carbon tax, carbon cap-and-trade and carbon offset. To solve the assumed uncertainties of product demand and number of products returned, robust optimization is adopted. The aim of the model proposed is to select which facility to open/operate, select a transportation mode and determine the quantity of shipped and substituted products. We show a numerical example of using the four carbon emission regulation policies.

Kaynakça

  • Ilgin MA, Gupta SM. Reverse Logistics. Editor: Gupta SM Reverse Supply Chains: Issues and Analysis, 1-60, Boca Raton, FL, USA, CRC Press, 2013.
  • Mohammed F, Selim SZ, Hassan A, Syed MN, “Multi-period planning of closed-loop supply chain with carbon policies under uncertainty”. Transportation Research Part D Transport and Environment, 51, 146-172, 2017.
  • Diabat A, Abdallah T, Al-refaie A,. Svetinovic D, Govindan K. “Strategic Closed-Loop Facility Location Problem”. IEEE Transactions on Engineering Management, 60(2), 398-408, 2013.
  • Jin M, Granda-Marulanda NA, Down I. “The impact of carbon policies on supply chain design and logistics of a major retailer”. Journal of Cleaner Prodoction, 85, 453-461, 2014.
  • Benjaafar S, Li Y, Daskin M. “Carbon footprint and the management of supply chains: Insights from simple models”. IEEE Transactions on Automation Science and Engineering, 10(1), 99-116, 2013.
  • Mohajeri A, Fallah M. “A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study”. Transportation Research Part D Transport and Environment, 48, 425-450, 2016.
  • He L, Hu C, Zhao D, Lu H, Fu X, Li Y. “Carbon emission mitigation through regulatory policies and operations adaptation in supply chains: theoretic developments and extensions”. Natural Hazards, 84(1), 179-207, 2016.
  • Fareeduddin M, Hassan A, Syed MN, Selim SZ. “The impact of carbon policies on closed-loop supply chain network design”. Procedia CIRP, 26, 335-340, 2015.
  • Gungor A, Gupta SM. “Issues in environmentally conscious manufacturing and product recovery: A survey”. Computers & Industrial Engineering, 36(4), 811-853, 1999.
  • Ilgin MA, Gupta SM. “Environmentally conscious manufacturing and product recovery ( ECMPRO ): A review of the state of the art”. Journal of Environmental Management, 91(3), 563-591, 2010.
  • Wei J, Zhao J. “Reverse channel decisions for a fuzzy closed-loop supply chain”. Applied Mathematical Modelling, 37(3), 1502-1513, 2013.
  • Hong IH, Yeh JS. “Modeling closed-loop supply chains in the electronics industry: A retailer collection application”. Transportation Research Part E: Logistics and Transportation Review, 48(4), 817-829, 2012.
  • Pishvaee MS, Jolai F, Razmi J. “A stochastic optimization model for integrated forward/reverse logistics network design”. Journal of Manufacturing Systems, 28(4), 107-114, 2009.
  • Pochampally KK, Nukala S, Gupta SM. Strategic planning models for reverse and closed-loop supply chains. Boca Raton, Florida: CRC Press, 2009.
  • Ferguson M. “Strategic and Tactical Aspects of Closed-Loop Supply Chains”. Foundations and Trends® in Technology, Information and Operations Management, 3(2), 101-200, 2009.
  • Jayaraman V, Guide VDR, Srivastava R. “A closed-loop logistics model for remanufacturing”. Journal of the Operational Research Society, 50(5), 497-508, 1999.
  • Beamon BM, Fernandes C. “Supply-chain network configuration for product recovery”. Production Planning & Control, 15(3), 270-281, 2004.
  • Demirel NÖ, Gökçen H. “A mixed integer programming model for remanufacturing in reverse logistics environment”. International Journal of Advanced Manufacturing Technology, 39(11-12), 1197-1206, 2008.
  • Özceylan E, Paksoy T. “A mixed integer programming model for a closed-loop supply-chain network”. International Journal of Production Research, 51(3), 718-734, 2013.
  • Kalaitzidou MA, Longinidis P, Georgiadis MC. “Optimal design of closed-loop supply chain networks with multifunctional nodes”. Computers & Chemical Engineering, 80, 73-91, 2015.
  • Listeş O. “A generic stochastic model for supply-and-return network design”. Computers & Operations Research, 34(2), 417-442, 2007.
  • Chouinard M, D’Amours S, Aït-Kadi D. “A stochastic programming approach for designing supply loops”. International Journal of Production Economics, 113(2), 657-677, 2008.
  • Soleimani H, Govindan K. “Reverse logistics network design and planning utilizing conditional value at risk”. European Journal of Operational Research, 237(2), 487-497, 2014.
  • Qin Z, Ji X. “Logistics network design for product recovery in fuzzy environment”. European Journal of Operational Research, 202(2), 479-490, 2010.
  • Pishvaee MS, Torabi SA. “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”. Fuzzy Sets and Systems, 161(20), 2668-2683, 2010.
  • Jindal A, Sangwan KS. “Closed loop supply chain network design and optimisation using fuzzy mixed integer linear programming model”. International Journal of Production Research, 52(14), 4156-4173, 2014.
  • Haddadsisakht A, Ryan SM. “Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax”. International Journal of Production Economics, 195, 118-131, 2018.
  • Ilgin MA, Gupta SM, Battaïa O. “Use of MCDM techniques in environmentally conscious manufacturing and product recovery: State of the art”. Journal of Manufacturing Systems, 37, 746-758, 2015.
  • Gupta SM, Ilgin MA. Multiple Criteria Decision Making Applications in Environmentally Conscious Manufacturing and Product Recovery. Boca Raton, Florida: CRC Press, 2018.
  • Amin SH, Zhang G. “Closed-loop supply chain network configuration by a multi-objective mathematical model”. International Journal of Business Performance and Supply Chain Modelling, 6(1), 1-15, 2014.
  • Shi J, Liu Z, Tang L, Xiong J. “Multi-objective optimization for a closed-loop network design problem using an improved genetic algorithm”. Applied Mathematical Modelling, 45, 14-30, 2016.
  • Nukala S, Gupta SM. “Strategic and tactical planning of a closed-loop supply chain network under uncertainty”. SPIE International Conference on Environmentally Conscious Manufacturing VI, Boston, USA, 01-03 October 2006.
  • Amin SH, Zhang G. “A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return”. Applied Mathematical Modelling, 37(6), 4165-4176, 2013.
  • Paksoy T, Pehlivan NY, Özceylan E. “Fuzzy Multi-Objective Optimization of a Green Supply Chain Network with Risk Management that Includes Environmental Hazards”. Human and Ecological Risk Assessment: An International Journal, 18(5), 1120-1151, 2012.
  • Pishvaee MS, Rabbani M, Torabi SA. “A robust optimization approach to closed-loop supply chain network design under uncertainty”. Applied Mathematical Modelling, 35(2), 637-649, 2011.
  • Özceylan E, Paksoy T. “Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty”. International Journal of Production Research, 52(8), 2363-2387, 2014.
  • Jindal A, Sangwan KS. “Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors”. Annals of Operations Research, 257(1-2), 95-120, 2017.
  • Zhen L, Huang L, Wang W. “Green and sustainable closed-loop supply chain network design under uncertainty”. Journal of Cleaner Prodoction, 227, 1195-1209, 2019.
  • Ahiska SS, Gocer F, King RE. “Heuristic inventory policies for a hybrid manufacturing/remanufacturing system with product substitution”. Computers &. Industrial Engineering, 114, 206-222, 2017.
  • Ghafarimoghadam A, Karimi A, Mousazadeh M, Pishvaee MS. “A robust optimisation model for remanufacturing network design problem with one-way substitution”. International Journal of Services and Operations Management, 24(4), 484-503, 2016.
  • Fahimnia B, Sarkis J, Dehghanian F, Banihashemi N, Rahman S. “The impact of carbon pricing on a closed-loop supply chain: An Australian case study”. Journal of Cleaner Prodoction, 59, 210-225, 2013.
  • Mohammed F, Hassan A, Selim SZ. “Carbon market sensitive robust optimization model for closed loop supply chain network design under uncertainty”. Journal of Physics: Conference Series, 1150(1), 1-10, 2019.
  • Shin H, Park S, Lee E, Benton WC. “A classification of the literature on the planning of substitutable products”. European Journal of Operational Research, 246(3), 686-699, 2015.
  • Lang JC. “Production and inventory management with substitutions”. Lecture Notes in Economics and Mathematical Systems, 636, 1-258, 2010.
  • Bayindir ZP, Erkip N, Güllü R. “Assessing the benefits of remanufacturing option under one-way substitution”. Journal of the Operational Research Society, 56(3), 286-296, 2005.
  • Bayindir ZP, Erkip N, Güllü R. “Assessing the benefits of remanufacturing option under one-way substitution and capacity constraint”. Computers & Operations Research, 34(2), 487-514, 2007.
  • Li Y, Chen J, Cai X. “Uncapacitated production planning with multiple product types, returned product remanufacturing, and demand substitution”. OR Spectrum, 28(1), 101-125, 2006.
  • Piñeyro P, Viera O. “The economic lot-sizing problem with remanufacturing and one-way substitution,” Int. J. Prod. Econ., 156, 167-168, 2010.
  • A. Choudhary, S. Sarkar, S. Settur, and M. K. Tiwari, “A carbon market sensitive optimization model for integrated forward-reverse logistics”. International Journal of Production Economics, 164, 433-444, 2015.
  • Mulvey JM, Vanderbei RJ, Zenios SA. “Robust Optimization of Large-Scale Systems”. Operations Research, 43(2), 264-281, 1995.
  • Yu C, Li H. “A robust optimization model for stochastic logistic problems”. International Journal of Production Economics, 64(1-3), 385-397, 2000.
  • Li HL, “An efficient method for solving linear goal programming problems”. Journal of Optimization Theory and Applications, 90(2), 465-469, 1996.
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Özel Sayı
Yazarlar

Murtadha Aldoukhi Bu kişi benim

Surendra Gupta Bu kişi benim

Yayımlanma Tarihi 31 Aralık 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 25 Sayı: 9

Kaynak Göster

APA Aldoukhi, M., & Gupta, S. (2019). A robust closed loop supply chain network design under different carbon emission policies. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 25(9), 1020-1032.
AMA Aldoukhi M, Gupta S. A robust closed loop supply chain network design under different carbon emission policies. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. Aralık 2019;25(9):1020-1032.
Chicago Aldoukhi, Murtadha, ve Surendra Gupta. “A Robust Closed Loop Supply Chain Network Design under Different Carbon Emission Policies”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 25, sy. 9 (Aralık 2019): 1020-32.
EndNote Aldoukhi M, Gupta S (01 Aralık 2019) A robust closed loop supply chain network design under different carbon emission policies. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 25 9 1020–1032.
IEEE M. Aldoukhi ve S. Gupta, “A robust closed loop supply chain network design under different carbon emission policies”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 25, sy. 9, ss. 1020–1032, 2019.
ISNAD Aldoukhi, Murtadha - Gupta, Surendra. “A Robust Closed Loop Supply Chain Network Design under Different Carbon Emission Policies”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 25/9 (Aralık 2019), 1020-1032.
JAMA Aldoukhi M, Gupta S. A robust closed loop supply chain network design under different carbon emission policies. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2019;25:1020–1032.
MLA Aldoukhi, Murtadha ve Surendra Gupta. “A Robust Closed Loop Supply Chain Network Design under Different Carbon Emission Policies”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 25, sy. 9, 2019, ss. 1020-32.
Vancouver Aldoukhi M, Gupta S. A robust closed loop supply chain network design under different carbon emission policies. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2019;25(9):1020-32.





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