Developing a multiproduct three-level cold supply chain considering quality evaluation function and pricing mechanism

Document Type : Article

Authors

Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

Abstract

Paying attention to cold supply chains is critical in light of rising global warming and public awareness of the issue. In addition, a lack of appropriate quality control in supply chains has resulted in significant waste in the industry. This research sought to create a three-level cold supply chain (firm, distribution center, and retailer) with a quality evaluation function. The chain has been modelled for a multiplicity of products and time periods. The parameters in this model are analyzed in three separate scenarios to reflect uncertainty. The model also includes direct delivery from the firm to the store. Various factors can affect the quality evaluation variables, which in this model are assigned to two main parameters: temperature and humidity. The quality of the products in this model is used to estimate their selling price. Due to the nonlinearity of the model, the Baron approach is applied in this work.

Keywords

References

References:
1. Solomon, S., Qin, D., Manning, M., et al., Climate Change 2007 - The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC (2007). https://www.ipcc.ch/report/ar4/wg1.
2. Hanna, E. "Radiative forcing of climate change: Expanding the concept and addressing uncertainties. By the National Research Council (NRC). National Academies Press, Washington DC, USA, 2005. 207 pp. Paperback", Weather, 62(4), pp. 109-119 (2007). DOI: 10.1002/wea.8.
3. Huang, Y.A., Weber, C.L., and Matthews, H.S. "Categorization of scope 3 emissions for streamlined enterprise carbon footprinting", Environ. Sci. Technol., 43(22), pp. 8509-8515 (2009). https://doi.org/10.1021/es901643a.
4. Environmental Protection Agency "Managing supply chain greenhouse gas emissions: Lessons learned for the road ahead", U.S. Environ. Prot. Agency, (December), p. 26 (2010).
5. Saif, A. and Elhedhli, S. "Cold supply chain design with environmental considerations: A simulationoptimization approach", Eur. J. Oper. Res., 251(1), pp. 274-287 (2016). https://doi.org/10.1016/j.ejor.2015.10.056.
6. Velders, G.J.M., Fahey, D.W., Daniel, J.S., et al. "The large contribution of projected HFC emissions to future climate forcing", Proc. Natl. Acad. Sci, 106(27), pp. 10949-10954 (2009). https://doi.org/10.1073/pnas.0902817106.
7. Bonney, M. and Jaber, M.Y. "Environmentally responsible  inventory models: Non-classical models for a nonclassical era", Int. J. Prod. Econ., 133(1), pp. 43-53 (2011). https://doi.org/10.1016/j.ijpe.2009.10.033.
8. Litto, R., Hayes, R.E., and Liu, B. "Catalytic combustion for reduction of fugitive methane emissions from natural gas compressor stations", Greenh. Gas Control Technol., 1, pp. 329-336 (2005). https://doi.org/10.1016/B978-008044704-9/50034-3.
9. Hariga, M., As'ad, R., and Shamayleh, A. "Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation", J. Clean. Prod., 166, pp. 1357-1371 (2017). https://doi.org/10.1016/j.jclepro.2017.08.105.
10. Yu, Y., Zhang, M., and Huo, B. "The impact of supply chain quality integration on green supply chain management and environmental performance", Total Qual. Manag. Bus. Excell., 30(9-10), pp. 1110-1125 (2019). https://doi.org/10.1080/14783363.2017.1356684.
11. Ramudhin, A., Chaabane, A., and Paquet, M. "Carbon market sensitive sustainable supply chain network design", Int. J. Manag. Sci. Eng. Manag., 5(1), pp. 30-38 (2010). https://doi.org/10.1080/17509653.2010.10671088.
12. Diabat, A. and Simchi-Levi, D. "A carbon-capped supply chain network problem", IEEM 2009 - IEEE Int. Conf. Ind. Eng. Eng. Manag., pp. 523-527 (2009). DOI: 10.1109/IEEM.2009.5373289.
13. Harris, I., Mumford, C., and Naim, M. "The multi-objective uncapacitated facility location problem for green logistics", 2009 IEEE Congr. Evol. Comput. CEC 2009, pp. 2732-2739 (2009). DOI: 10.1109/CEC.2009.4983285.
14. Bin, Y. and Jun, H. "An analysis on green supply chain management in E-commerce under the economic globalization.", Bus. Intell. and Financial Eng. Int. Conf. (2009). DOI: 10.1109/BIFE.2009.140.
15. Bojarski, A.D., Lainez, J.M., Espuna, A., et al. "Incorporating environmental impacts and regulations in a holistic supply chains modeling: An LCA approach", Comput. Chem. Eng., 33(10), pp. 1747-1759 (2009). https://doi.org/10.1016/j.compchemeng.2009.04.009.
16. Wang, W. and Liu, X. "China cold-chain logistics energy consumption status and the countermeasures- (China Business and Market) 2011", China Circ. Econ., 25(10), pp. 29-33 (2011).
17. Chaabane, A., Ramudhin, A., and Paquet, M. "Design of sustainable supply chains under the emission trading scheme", Int. J. Prod. Econ., 135(1), pp. 37-49 (2012). https://doi.org/10.1016/j.ijpe.2010.10.025.
18. Hsiao, Y.H., Chen, M.C., and Chin, C.L. "Distribution planning for perishable foods in cold chains with quality concerns: Formulation and solution procedure", Trends Food Sci. Technol., 61, pp. 80-93 (2017). https://doi.org/10.1016/j.tifs.2016.11.016.
19. Catala, L.P., Moreno, M.S., Blanco, A.M., et al. "A bi-objective optimization model for tactical planning in the pome fruit industry supply chain", Comput. Electron. Agric., 130, pp. 128-141 (2016). https://doi.org/10.1016/j.compag.2016.10.008.
20. Behzadi, G., Justin, M., Sullivan, O., et al. "International journal of production economics robust and resilient strategies for managing supply disruptions in an agribusiness supply chain", Int. J. Prod. Econ., 191(June), pp. 207-220 (2017). https://doi.org/10.1016/j.ijpe.2017.06.018.
21. Hua, G., Cheng, T.C.E., and Wang, S. "Managing carbon footprints in inventory control", SSRN Electron. J (2012). 
22. Bouchery, Y., Ghaffari, A., Jemai, Z., et al. "Including sustainability criteria into inventory models", Eur. J. Oper. Res., 222(2), pp. 229-240 (2012). https://doi.org/10.1016/j.ejor.2012.05.004.
23. Benjaafar, S., Li, Y., and Daskin, M. "Carbon footprint and the management of supply chains", INFORMS Annu. Meet. San Diego CA., 10(1), pp. 99- 116 (2013). DOI: 10.1109/TASE.2012.2203304.
24. Chen, X., Benjaafar, S., and Elomri, A. "The carbonconstrained EOQ", Oper. Res. Lett., 41(2), pp. 172- 179 (2013). https://doi.org/10.1016/j.orl.2012.12.003.
25. Absi, N., Dauzere-Peres, S., Kedad-Sidhoum, S., et al. "Lot sizing with carbon emission constraints", Eur. J. Oper. Res., 227(1), pp. 55-61 (2013). https://doi.org/10.1016/j.ejor.2012.11.044.
26. Jaber, M.Y. "Learning and forgetting models and their applications", In Handbook of Industrial and Systems Engineering, Second Edition, pp. 535-566 (December 15, 2013). DOI: 10.1201/9781420038347.ch30.
27. Zanoni, S., Bettoni, L., and Glock, C.H., "Energy implications in a two-stage production system with controllable production rates", Int. J. Prod. Econ., 149, pp. 164-171 (2014). https://doi.org/10.1016/j.ijpe.2013.06.025.
28. Hammami, R., Nouira, I., and Frein, Y. "Carbon emissions in a multi-echelon productioninventory model with lead time constraints", Int. J. Prod. Econ., 164, pp. 292-307 (2015). https://doi.org/10.1016/j.ijpe.2014.12.017.
29. Konur, D. and Schaefer, B. "Integrated inventory control and transportation decisions under carbon emissions regulations: LTL vs. TL carriers", Transp. Res. Part E Logist. Transp. Rev., 68, pp. 14-38 (2014). https://doi.org/10.1016/j.tre.2014.04.012.
30. Bozorgi, A., Pazour, J., and Nazzal, D. "A new inventory model for cold items that considers costs and emissions", Int. J. Prod. Econ., 155, pp. 114-125 (2014). https://doi.org/10.1016/j.ijpe.2014.01.006.
31. Bozorgi, A. "Multi-product inventory model for cold items with cost and emission consideration", Int. J. Prod. Econ., 176, pp. 123-142 (2016). https://doi.org/10.1016/j.ijpe.2016.03.011.
32. Miao, X., Zhou, X. and Lin, L. "Study on optimization for cold-chain logistics distribution of 3PL", Oper. Manag., 20, pp. 32-38 (2011). Corpus ID: 63121691.
33. Li, H., Zhang, L., Lv, T., et al. "The twoechelon time-constrained vehicle routing problem in linehaul-delivery systems", Transp. Res. Part B Methodol., 94, pp. 169-188 (2016). https://doi.org/10.1016/j.trb.2016.09.012.
34. Marchi, B., Zanoni, S., Ferretti, I., et al. "Stimulating investments in energy efficiency through supply chain integration", Energies., 11(4), p. 858 (2018). https://doi.org/10.3390/en11040858.
35. Marchi, B., Zanoni, S., Zavanella, L.E., et al. "Green supply chain with learning in production and environmental investments", IFAC-PapersOnLine., 51(11), pp. 1738-1743 (2018). https://doi.org/10.1016/j.ifacol.2018.08.205.
36. Gwanpua, S.G., Verboven, P., Leducq, D., et al. "The FRISBEE tool, a software for optimising the trade-off between food quality, energy use, and global warming impact of cold chains", J. Food Eng., 148, pp. 2-12 (2015). https://doi.org/10.1016/j.jfoodeng.2014.06.021.
37. Hoang, H.M., Flick, D., Derens, E., et al. "Combined deterministic and stochastic approaches for modelling the evolution of food products along the cold chain. Part II: A case study", Int. J. Refrig., 35(4), pp. 915-926 (2012). https://doi.org/10.1016/j.ijrefrig.2011.12.009.
38. Gonela, V. "Stochastic optimization of hybrid electricity supply chain considering carbon emission schemes", Sustain. Prod. Consum., 14, pp. 136-151 (2018).  https://doi.org/10.1016/j.spc.2018.02.004.
39. Jiang, D.L. and Yang, X.L. "Genetic algorithm for continuous location problem of physical distribution center for decaying products", Xitong Gongcheng Lilun yu Shijian/System Eng. Theory Pract., 23(2), p. 62 (2003). https://doi.org/10.12011/1000.
40. Wang, H., Wang, L., and Yong, Y. "Distribution of perishable food based on models with time windows", Ind. Eng. J., 3(11), pp. 127-130 (2008). https://doi.org/10.3390/math12020332.
41. Wang, Z. and Zhao, F. "Establishment of route optimization model of refrigerated food transportation", Logist. Technol., 1, pp. 85-88 (2010). 10.1109/ICSSSM. 2012.6252224.
42. Yang, J., Wang, L., Zheng, N., et al. "Study on the distribution center location problem of perishable product with multi-usage", Chin J Manag Sci., 1, pp. 91-99 (2011). http://www.zgglkx.com/EN/Y2011/V19/I1/91.
43. Govindan, K. "Sustainable consumption and production in the food supply chain: A conceptual framework", Int. J. Prod. Econ., 195, pp. 419-431 (2018). https://doi.org/10.1016/j.ijpe.2017.03.003.
44. Rizou, M., Galanakis, I.M., Aldawoud, T.M.S., et al. "Safety of foods, food supply chain and environment within the COVID-19 pandemic", Trends Food Sci. Technol., 102, pp. 293-299 (2020). https://doi.org/10.1016/j.tifs.2020.06.008.
45. Wang, F., Lai, X., and Shi, N. "A multiobjective optimization for green supply chain network design Keywords: Green supply chain management Network design multi-objective optimization", Decis. Support Syst., 51, pp. 262-269 (2011). https://doi.org/10.1016/j.dss.2010.11.020.
46. Xu, Z., Sun, D.W., Zeng, X.A., et al. "Research developments in methods to reduce the carbon footprint of the food system: A review", Crit. Rev. Food Sci. Nutr, 1(2), pp. 1270-1286 (2015). https://doi.org/10.1080/10408398.2013.821593.
47. Toptal, A.,  Ozlu, H., and Konur, D. "Joint decisions on inventory replenishment and emission reduction investment under different emission regulations", Int. J. Prod. Res., 52(1), pp. 243-269 (2014). https://doi.org/10.1080/00207543.2013.836615.
48. Stellingwerf, H.M., Laporte, G., Cruijssen, F.C.A.M., et al. "Quantifying the environmental and economic benefits of cooperation: A case study in temperature-controlled food logistics", Transp. Res. Part D Transp. Environ., 65, pp. 178-193 (2018). https://doi.org/10.1016/j.trd.2018.08.010.
49. Biel, K. and Glock, C.H. "Systematic literature review of decision support models for energy-efficient production planning", Comput. Ind. Eng., 101, pp. 243-259 (2016). https://doi.org/10.1016/j.cie.2016.08.021.
50. Bazan, E., Jaber, M.Y., and Zanoni, S. "Carbon emissions and energy effects on a two-level manufacturerretailer closed-loop supply chain model with remanufacturing subject to different coordination mechanisms", Int. J. Prod. Econ., 183, pp. 394-408 (2017). https://doi.org/10.1016/j.ijpe.2016.07.009.
51. Wang, C. and Huang, R. "Comments on 'vendormanaged inventory with consignment stock agreement for single vendor-single buyer under the emissiontrading scheme"', Int. J. Prod. Res., 54(13), pp. 4081- 4086 (2016). https://doi.org/10.1080/00207543.2015.1106610.
52. Li, Y., Lim, M.K., and Tseng, M.L. "A green vehicle routing model based on modified particle swarm optimization for cold chain logistics", Ind. Manag. Data Syst., 119(3), pp. 473-494 (2019). https://doi.org/10.1108/IMDS-07-2018-0314.
53. Kancharla, S.R. and Ramadurai, G. "Incorporating driving cycle based fuel consumption estimation in green vehicle routing problems", Sustain. Cities Soc., 40, pp. 214-221 (2018). https://doi.org/10.1016/j.scs.2018.04.016.
54. Xiao, Y. and Konak, A. "A genetic algorithm with exact dynamic programming for the green vehicle routing and scheduling problem", J. Clean. Prod., 167, pp. 1450-1463 (2018). https://doi.org/10.1016/j.jclepro.2016.11.115.
55. Ahn, K. and Rakha, H. "The effects of route choice decisions on vehicle energy consumption and emissions", Transp. Res. Part D Transp. Environ., 13(3), pp. 151- 167 (2008). https://doi.org/10.1016/j.trd.2008.01.005.
56. Leng, L., Zhang, C., Zhao, Y., et al. "Biobjective low-carbon location-routing problem for cold chain logistics: Formulation and heuristic approaches", J. Clean. Prod., 273, p. 122801 (2020). https://doi.org/10.1016/j.jclepro.2020.122801.
57. Chen, W.T. and Hsu, C.I. "Greenhouse gas emission estimation for temperature-controlled food distribution systems", J. Clean. Prod., 104, pp. 139-147 (2015). https://doi.org/10.1016/j.jclepro.2015.05.038.
58. Hoen, K.M.R., Tan, T., Fransoo, J.C., et al. "Effect of carbon emission regulations on transport mode selection under stochastic demand", Flex. Serv. Manuf. J., 26(1-2), pp. 170-195 (2014). DOI: 10.1007/s10696- 012-9151-6.
59. Jaber, M.Y., Glock, C.H., and El Saadany, A.M.A. "Supply chain coordination with emissions reduction incentives", Int. J. Prod. Res., 51(1), pp. 69-82 (2013). https://doi.org/10.1080/00207543.2011.651656.
60. Bozorgi, A., Zabinski, J., Pazour, J., et al. "Cold supply chains and carbon emissions: Recent works and recommendations", International Journal of Production Economics, 155, pp. 1-15 (2014). https://doi.org/10.1016/j.ijpe.2014.01.006.
61. Babagolzadeh, M., Shrestha, A., Abbasi, B., et al. "Sustainable cold supply chain management under demand uncertainty and carbon tax regulation", Transp. Res. Part D Transp. Environ., 80, p. 102245 (2020). https://doi.org/10.1016/j.trd.2020.102245.
62. Yakavenka, V., Mallidis, I., Vlachos, D., et al. "Development of a multi-objective model for the design of sustainable supply chains: the case of perishable food products", Ann. Oper. Res., 294(1), pp. 593-621 (2020). https://doi.org/10.1007/s10479-019-03434-5.
63. Wang, S., Sun, H., Mou, J., et al. "Optimization and efficiency of multi-temperature joint distribution of cold chain products: Comparative study based on cold accumulation mode and mechanical", En.Cnki.Com.Cn, 33(3), pp. 146-153 (2016). https://doi.org/10.3969/j.issn.1002-0268.2016.03.024.
64. Wang, X. and Li, D. "A dynamic product quality evaluation based pricing model for perishable food supply chains", Omega, 40(6), pp. 906-917 (2012). https://doi.org/10.1016/j.omega.2012.02.001.
65. Ferguson, M. and Ketzenberg, M.E. "Information sharing to improve retail product freshness of perishables", Prod. Oper. Manag., 15(1), pp. 57-73 (2006). https://doi.org/10.1111/j.1937-5956.2006.tb00003.x.
66. Pineau, S., Brockhoff, P.B., Escher, F., et al. "A comprehensive approach to evaluate the freshness of strawberries and carrots", Postharvest Biol. Technol., 45(1), pp. 20-29 (2007). https://doi.org/10.1016/j.postharvbio.2007.02.001.
67. Taoukis, P.S. and Labuza, T.P. "Applicability of timetemperature indicators as shelf life Monitors of food products", J. Food Sci., 54(4), pp. 783-788 (1989). https://doi.org/10.1111/j.1365-2621.1989.tb07882.x.
68. Blackburn, J. and Scudder, G. "Supply chain strategies for perishable products: The case of fresh produce", Prod. Oper. Manag., 18(2), pp. 129-137 (2009). https://doi.org/10.1111/j.1937-5956.2009.01016.x.
69. Fu, B. and Zabuza, Th. P. "Shelf-life prediction: Theory and application", Food control, 4(3), pp. 125-133 (1993). https://doi.org/10.1016/0956-7135(93)90298-3.
70. Lytou, A., Panagou, E.Z., and Nychas, G.J.E. "Corrigendum to development of a predictive model for the growth kinetics of aerobic microbial population on pomegranate marinated chicken breast fillets under isothermal and dynamic temperature conditions", Food Microbiol., 58, p. 148 (2016). https://doi.org/10.1016/j.fm.2015.11.009.
71. Song, H., Kim, J., Kim, B.S., et al. "Development of a food temperature prediction model for real time food quality assessment", Int. J. Refrig., 98, pp. 468-479 (2019). https://doi.org/10.1016/j.ijrefrig.2018.11.032.
72. Raab, V., Bruckner, S., Beierle, E., et al. "Generic model for the prediction of remaining shelf life in support of cold chain management in pork and poultry supply chains", J. Chain Netw. Sci., 8(1), pp. 59-73 (2008). https://doi.org/10.3920/JCNS2008.x089.
73. Van der Sman, R.G.M. "Simple model for estimating heat and mass transfer in regular-shaped foods", J. Food Eng., 60(4), pp. 383-390 (2003). https://doi.org/10.1016/S0260-8774(03)00061-X.
74. Chan, F.T.S., Wang, Z.X., Goswami, A., et al. "Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations", Int. J. Prod. Res., 58(17), pp. 5155-5174 (2020). https://doi.org/10.1080/00207543.2019.1701209.
75. Giri, B.C. and Masanta, M. "Developing a closedloop supply chain model with price and quality dependent demand and learning in production in a stochastic environment", Int. J. Syst. Sci. Oper. Logist., 7(2), pp. 147-163 (2020). https://doi.org/10.1080/23302674.2018.1542042.
76. Zhang, M., Guo, H., Huo, B., et al. "Linking supply chain quality integration with mass customization and product modularity", Int. J. Prod. Econ., 207, pp. 227-235 (2019). https://doi.org/10.1016/j.ijpe.2017.01.011.
77. Mercier, S., Villeneuve, S., Mondor, M., et al. "Time-temperature management along the food cold chain: A review of recent developments", Compr. Rev. Food Sci. Food Saf., 16(4), pp. 647-667 (2017). https://doi.org/10.1111/1541-4337.12269.
78. "Cargo Handbook-the world's largest cargo transport guidelines website", https://www.cargohandbook.com/Welcome-to- CargoHandbook.
79. Sahinidis, N.V. "BARON: A general purpose global optimization software package", J. Glob. Optim., 8(2), pp. 201-205 (1996). https://doi.org/10.1007/BF00138693.
80. Fibich, G., Gavious, A., and Lowengart, O. "Explicit solutions of optimization models and differential games with nonsmooth (asymmetric) reference-price effects", Oper. Res., 51(5), pp. 721-734 (2003). https://doi.org/10.1287/opre.51.5.721.16758.
81. Rong, A., Akkerman, R., and Grunow, M. "An optimization approach for managing fresh food quality throughout the supply chain", Int. J. Prod. Econ., 131(1), pp. 421-429 (2011). https://doi.org/10.1016/j.ijpe.2009.11.026.
Scientia Iranica
Volume 31, Issue 18
Transactions on Industrial Engineering (E)
November and December 2024
Pages 1638-1658

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  • Receive Date: 06 May 2020
  • Revise Date: 30 October 2021
  • Accept Date: 03 January 2022

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