[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Log in

Multi-period multi-scenario optimal design for closed-loop supply chain network of hazardous products with consideration of facility expansion

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Increased concern for the environment has led to urgent need to design the closed-loop supply chain network of hazardous products economically and ecologically. In this paper, we focus on the optimal design problem of multi-period closed-loop supply chain network of hazardous products considering uncertain demands and returns, expandable facility capacities and social acceptable risk simultaneously. In each period, the built facilities have the ability to expand within a certain scope. The problem is formulated as a mixed-integer nonlinear programming model, which can determine the number, location and expansion scale of the facilities and the forward and reverse logistics quantities between the facilities in each period simultaneously. The goal is to minimize the expected cost over the multi-period planning horizon, including the facilities building, operating and expansion costs and the costs related to manufacturing, collection, processing, recovery and transportation. In order to solve the proposed model, two classes of dummy variables are introduced to equivalently transform it into a mixed-integer linear programming, which can be optimally solved by LINGO. A case study is presented to illustrate the validity of the proposed model. The dynamic design with expansion strategy addressed in this paper is compared with two different strategies of static design and dynamic design without expansion. The results highlight that the dynamic design with expansion strategy has the advantages in saving expenses and raising the average expected collection rate of hazardous wastes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Amin SH, Zhang G (2013) A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Appl Math Model 37(6):4165–4176

    Article  MathSciNet  Google Scholar 

  • Carle MA, Martel A, Zufferey N (2012) The CAT metaheuristic for the solution of multi-period activity-based supply chain network design problems. Int J Prod Econ 139(2):664–677

    Article  Google Scholar 

  • Fattahi M, Mahootchi M, Govindan K, Husseini SMM (2015) Dynamic supply chain network design with capacity planning and multi-period pricing. Transp Res E Logist 81:169–202

    Article  Google Scholar 

  • Hafezalkotob A, Khalili-Damghani K, Ghashami SS (2016) A three-echelon multi-objective multi-period multi-product supply chain network design problem: a goal programming approach. J Optim Ind Eng 10(21):67–78

    Google Scholar 

  • Hatefi SM, Jolai F (2014) Robust and reliable forward–reverse logistics network design under demand uncertainty and facility disruptions. Appl Math Model 38(9):2630–2647

    Article  MathSciNet  Google Scholar 

  • Jabbarzadeh A, Fahimnia B, Seuring S (2014) Dynamic supply chain network design for the supply of blood in disasters: a robust model with real world application. Transp Res E Logist 70(1):225–244

    Article  Google Scholar 

  • Kannan G, Sasikumar P, Devika K (2010) A genetic algorithm approach for solving a closed loop supply chain model: a case of battery recycling. Appl Math Model 34(3):655–670

    Article  MathSciNet  Google Scholar 

  • Kaya O, Urek B (2016) A mixed integer nonlinear programming model and heuristic solutions for location, inventory and pricing decisions in a closed loop supply chain. Comput Oper Res 65:93–103

    Article  MathSciNet  Google Scholar 

  • Ko HJ, Evans GW (2007) A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput Oper Res 34(2):346–366

    Article  Google Scholar 

  • Liu B (2014) Uncertainty theory, 4th edn. Springer, Berlin

    Google Scholar 

  • Ma H, Li X (2018) Closed-loop supply chain network design for hazardous products with uncertain demands and returns. Appl Soft Comput 68:889–899

    Article  Google Scholar 

  • Mohammed F, Selim SZ, Hassan A, Syed MN (2017) Multi-period planning of closed-loop supply chain with carbon policies under uncertainty. Transp Res D Transp Environ 51:146–172

    Article  Google Scholar 

  • Özceylan E, Paksoy T, Bektaş T (2014) Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing. Transp Res E Logist 61:142–164

    Article  Google Scholar 

  • Pishvaee MS, Rabbani M, Torabi SA (2011) A robust optimization approach to closed-loop supply chain network design under uncertainty. Appl Math Model 35(2):637–649

    Article  MathSciNet  Google Scholar 

  • Sasikumar P, Haq AN (2011) Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling. Int J Prod Res 49(11):3363–3385

    Article  Google Scholar 

  • Soleimani H, Kannan G (2015) A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks. Appl Math Model 39(14):3990–4012

    Article  MathSciNet  Google Scholar 

  • Subramanian P, Ramkumar N, Narendran TT, Ganesh K (2013) A bi-objective network design model for multi-period, multi-product closed-loop supply chain. J Ind Prod Eng 30(4):264–280

    Google Scholar 

  • Üster H, Hwang SO (2016) Closed-loop supply chain network design under demand and return uncertainty. Transp Sci 51(4):1063–1085

    Article  Google Scholar 

  • Yassen ET, Ayob M, Nazri MZA, Sabar NR (2015) Meta-harmony search algorithm for the vehicle routing problem with time windows. Inf Sci 325:140–158

    Article  Google Scholar 

  • Zeballos LJ, Méndez CA, Barbosa-Povoa AP, Novais AQ (2014) Multi-period design and planning of closed-loop supply chains with uncertain supply and demand. Comput Chem Eng 66:151–164

    Article  Google Scholar 

  • Zhalechian M, Tavakkoli-Moghaddam R, Zahiri B, Mohammadi M (2016) Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transp Res E Logist 89:182–214

    Article  Google Scholar 

  • Zhang ZH, Unnikrishnan A (2016) A coordinated location-inventory problem in closed-loop supply chain. Transp Res B Methodol 89:127–148

    Article  Google Scholar 

  • Zhao J, Huang L, Lee DH, Peng Q (2016) Improved approaches to the network design problem in regional hazardous waste management systems. Transp Res E Logist 88:52–75

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (Nos. 71722007 & 71931001), the Funds for First-class Discipline Construction (XK1802-5) and the Fundamental Research Funds for the Central Universities (buctrc201926).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiang Li.

Ethics declarations

Conflict of interest

Author Hongguang Ma declares that he has no conflict of interest. Author Xiang Li declares that he has no conflict of interest. Author Yankui Liu declares that he has no conflict of interest.

Human and animal rights

This article does not contain any studies with human or animal participants performed by the author.

Additional information

Communicated by Y. Ni.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, H., Li, X. & Liu, Y. Multi-period multi-scenario optimal design for closed-loop supply chain network of hazardous products with consideration of facility expansion. Soft Comput 24, 2769–2780 (2020). https://doi.org/10.1007/s00500-019-04435-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-04435-z

Keywords

Navigation