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Mathematical Problems in Engineering
Volume 2018, Article ID 9376080, 18 pages
https://doi.org/10.1155/2018/9376080
Research Article

A Dynamic Programming-Based Sustainable Inventory-Allocation Planning Problem with Carbon Emissions and Defective Item Disposal under a Fuzzy Random Environment

School of Economics and Management, Hebei University of Technology, Tianjin 300401, China

Correspondence should be addressed to Yanfang Ma; nc.ude.tubeh@gnafnayam

Received 19 May 2017; Accepted 15 January 2018; Published 21 February 2018

Academic Editor: Jason Gu

Copyright © 2018 Kai Kang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. V. Hashemi, M. Chen, and L. Fang, “Process planning for closed-loop aerospace manufacturing supply chain and environmental impact reduction,” Computers & Industrial Engineering, vol. 75, no. 1, pp. 87–95, 2014. View at Publisher · View at Google Scholar · View at Scopus
  2. S. M. Mousavi, N. Alikar, S. T. A. Niaki, and A. Bahreininejad, “Optimizing a location allocation-inventory problem in a two-echelon supply chain network: a modified fruit fly optimization algorithm,” Computers & Industrial Engineering, vol. 87, pp. 543–560, 2015. View at Publisher · View at Google Scholar · View at Scopus
  3. R. Kruse and K. D. Meyer, Statistics with vague data, Theory and Decision Library. Series B: Mathematical and Statistical Methods, D. Reidel Publishing Co., Dordrecht, Holland, 1987. View at MathSciNet
  4. S. Priyan and R. Uthayakumar, “Two-echelon multi-product multi-constraint product returns inventory model with permissible delay in payments and variable lead time,” Journal of Manufacturing Systems, vol. 36, article no. 304, pp. 244–262, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. H. Hu, H. Xiong, Y. You, and W. Yan, “A Mixed Integer Programming Model for Supplier Selection and Order Allocation Problem with Fuzzy Multiobjective,” Scientific Programming, vol. 2016, Article ID 9346781, 2016. View at Publisher · View at Google Scholar · View at Scopus
  6. G. T. Temur, “A novel multi attribute decision making approach for location decision under high uncertainty,” Applied Soft Computing, vol. 40, pp. 674–682, 2016. View at Publisher · View at Google Scholar · View at Scopus
  7. M. A. Alhaj, D. Svetinovic, and A. Diabat, “A carbon-sensitive two-echelon-inventory supply chain model with stochastic demand,” Resources, Conservation & Recycling, vol. 108, pp. 82–87, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. H.-C. Li, “Optimal delivery strategies considering carbon emissions, time-dependent demands and demand-supply interactions,” European Journal of Operational Research, vol. 241, no. 3, pp. 739–748, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. H. Salehi, A. A. Taleizadeh, and R. Tavakkolimoghaddam, “An EOQ model with random disruption and partial backordering,” International Journal of Production Research, vol. 54, no. 9, pp. 1–10, 2016. View at Google Scholar · View at Scopus
  10. S. K. Jakhar, “Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry,” Journal of Cleaner Production, vol. 87, no. 1, pp. 391–413, 2015. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Ma, F. Yan, K. Kang, and X. Wei, “A novel integrated production-distribution planning model with conflict and coordination in a supply chain network,” Knowledge-Based Systems, vol. 105, pp. 119–133, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. K. Shaw, M. Irfan, R. Shankar, and S. S. Yadav, “Low carbon chance constrained supply chain network design problem: a benders decomposition based approach,” Computers & Industrial Engineering, vol. 98, pp. 483–497, 2016. View at Publisher · View at Google Scholar · View at Scopus
  13. S. A. Torabi, E. Hassini, and M. Jeihoonian, “Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing,” Transportation Research Part E: Logistics and Transportation Review, vol. 79, pp. 128–144, 2015. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Diabat and M. Al-Salem, “An integrated supply chain problem with environmental considerations,” International Journal of Production Economics, vol. 164, pp. 330–338, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. D. French, “Kyoto protocol to the united nations framework convention on climate change,” in Proceedings of the Review of European Community International Envi- ronmental Law 7 (2, vol. 7, pp. 214–217, 1998.
  16. Y. Liu, “Uncertain random programming with applications,” Fuzzy Optimization and Decision Making. A Journal of Modeling and Computation Under Uncertainty, vol. 12, no. 2, pp. 153–169, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. B. Pal, S. S. Sana, and K. S. Chaudhuri, “Joint pricing and ordering policy for two echelon imperfect production inventory model with two cycles,” International Journal of Production Economics, vol. 155, pp. 229–238, 2014. View at Publisher · View at Google Scholar
  18. M. Radhi and G. Zhang, “Optimal configuration of remanufacturing supply network with return quality decision,” International Journal of Production Research, vol. 54, no. 5, pp. 1–16, 2015. View at Google Scholar
  19. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, Perth, Australia, December 1995. View at Scopus
  20. M. A. Rodriguez, A. R. Vecchietti, I. Harjunkoski, and I. E. Grossmann, “Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models,” Computers & Chemical Engineering, vol. 62, pp. 194–210, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. S. M. Mousavi, S. T. A. Niaki, A. Bahreininejad, and S. N. Musa, “Multi-item multiperiodic inventory control problem with variable demand and discounts: A particle swarm optimization algorithm,” The Scientific World Journal, vol. 2014, Article ID 136047, 16 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  22. A. H. Nobil and A. H. A. Sedigh, “A multi-machine multi-product EPQ problem for an imperfect manufacturing system considering utilization and allocation decisions,” Expert Systems with Applications, vol. 56, pp. 310–319, 2016. View at Publisher · View at Google Scholar · View at Scopus
  23. J. N. Roul, K. Maity, S. Kar, and M. Maiti, “Multi-item reliability dependent imperfect production inventory optimal control models with dynamic demand under uncertain resource constraint,” International Journal of Production Research, vol. 53, no. 16, pp. 1–24, 2015. View at Google Scholar
  24. J. Zhou, F. Yang, and K. Wang, “Multi-objective optimization in uncertain random environments,” Fuzzy Optimization and Decision Making, vol. 13, no. 4, pp. 397–413, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  25. A. Tognetti, G. R. Pan, and S. M. Wagner, “Green supply chain network optimization and the trade-off between environmental and economic objectives,” International Journal of Production Economics, vol. 170, no. 1, pp. 385–392, 2015. View at Google Scholar
  26. T.-Y. Lin, “Coordination policy for a two-stage supply chain considering quantity discounts and overlapped delivery with imperfect quality,” Computers & Industrial Engineering, vol. 66, no. 1, pp. 53–62, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. S. T. Zhao, K. Wu, and X.-M. Yuan, “Optimal production-inventory policy for an integrated multi-stage supply chain with time-varying demand,” European Journal of Operational Research, vol. 255, no. 2, pp. 364–379, 2016. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  28. K. Kang, W. Pu, Y. Ma, and X. Wei, “A novel inventory and distribution planning model with non-conforming items disposal under fuzzy random environment,” Advances in Intelligent Systems and Computing, vol. 502, pp. 1191–1201, 2017. View at Publisher · View at Google Scholar · View at Scopus
  29. X. Zhou, W. Pedrycz, Y. Kuang, and Z. Zhang, “Type-2 fuzzy multi-objective DEA model: An application to sustainable supplier evaluation,” Applied Soft Computing, vol. 46, pp. 424–440, 2016. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Tang, S. Ji, and L. Jiang, “The design of a sustainable location-routing-inventory model considering consumer environmental behavior,” Sustainability, vol. 8, no. 3, article no. 211, 2016. View at Publisher · View at Google Scholar · View at Scopus
  31. H. Ke, T. Su, and Y. Ni, “Uncertain random multilevel programming with application to production control problem,” Soft Computing, vol. 19, no. 6, pp. 1739–1746, 2015. View at Publisher · View at Google Scholar · View at Scopus
  32. J. Xu, J. Meng, Z. Zeng, S. Wu, and M. Shen, “Resource sharing-based multiobjective multistage construction equipment allocation under fuzzy environment,” Journal of Construction Engineering and Management, vol. 139, no. 2, pp. 161–173, 2013. View at Publisher · View at Google Scholar · View at Scopus
  33. K. Veeramachaneni, T. Peram, C. Mohan, and L. A. Osadciw, “Optimization Using Particle Swarms with Near Neighbor Interactions,” in Genetic and Evolutionary Computation — GECCO 2003, vol. 2723 of Lecture Notes in Computer Science, pp. 110–121, Springer Berlin Heidelberg, Berlin, Heidelberg, 2003. View at Publisher · View at Google Scholar
  34. A. Mohajeri and M. Fallah, “A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study,” Transportation Research Part D: Transport and Environment, vol. 48, pp. 425–450, 2016. View at Publisher · View at Google Scholar · View at Scopus
  35. J. Xu, Z. Zeng, B. Han, and X. Lei, “A dynamic programming-based particle swarm optimization algorithm for an inventory management problem under uncertainty,” Engineering Optimization, vol. 45, no. 7, pp. 851–880, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  36. A. Chaabane, A. Ramudhin, and M. Paquet, “Design of sustainable supply chains under the emission trading scheme,” International Journal of Production Economics, vol. 135, no. 1, pp. 37–49, 2012. View at Google Scholar
  37. P. Pongchairerks and V. Kachitvichyanukul, “Particle swarm optimization algorithm with multiple social learning structures,” International Journal of Operational Research, vol. 6, no. 2, pp. 176–194, 2009. View at Publisher · View at Google Scholar · View at Scopus
  38. M. H. Gorji, M. Setak, and H. Karimi, “Optimizing inventory decisions in a two-level supply chain with order quantity constraints,” Applied Mathematical Modelling, vol. 38, no. 3, pp. 814–827, 2014. View at Publisher · View at Google Scholar · View at Scopus
  39. R. Li and B.-J. Tang, “Initial carbon quota allocation methods of power sectors: a China case study,” Natural Hazards, vol. 84, no. 2, pp. 1075–1089, 2016. View at Publisher · View at Google Scholar · View at Scopus
  40. R. Qiu and Y. Wang, “Supply chain network design under demand uncertainty and supply disruptions: a distributionally robust optimization approach,” Scientific Programming, vol. 2016, Article ID 3848520, 15 pages, 2016. View at Publisher · View at Google Scholar
  41. N. Road, Environmental data for international cargo transport & road transport. ntm, 2008.
  42. M. Khan, M. Y. Jaber, S. Zanoni, and L. Zavanella, “Vendor managed inventory with consignment stock agreement for a supply chain with defective items,” Applied Mathematical Modelling, vol. 40, no. 15-16, pp. 7102–7114, 2016. View at Publisher · View at Google Scholar · View at Scopus
  43. S. Heilpern, “The expected value of a fuzzy number,” Fuzzy Sets and Systems, vol. 47, no. 1, pp. 81–86, 1992. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  44. S. Pazhani, J. A. Ventura, and A. Mendoza, “A serial inventory system with supplier selection and order quantity allocation considering transportation costs,” Applied Mathematical Modelling, vol. 40, no. 1, pp. 612–634, 2016. View at Publisher · View at Google Scholar · View at Scopus
  45. M. Varsei and S. Polyakovskiy, “Sustainable supply chain network design: A case of the wine industry in Australia,” OMEGA - The International Journal of Management Science, vol. 66, pp. 236–247, 2017. View at Publisher · View at Google Scholar · View at Scopus
  46. J. Rezaei and M. Davoodi, “Multi-objective models for lot-sizing with supplier selection,” International Journal of Production Economics, vol. 130, no. 1, pp. 77–86, 2011. View at Publisher · View at Google Scholar · View at Scopus