A Facility Location Problem in a Green Closed-Loop Supply Chain Network Design by Considering Defective Products

Subject Areas : Layout Planning

Zahra Zanjani Foumani ¹ , Ensieh Ghaedy heidary ² , Amir Aghsami ³ , Masoud Rabbani ⁴

1 - School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 - School of Industrial & Systems Engineering, College of Engineering, University of Tehran
3 - School of Industrial & Systems Engineering, College of Engineering, University of Tehran
4 - School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran

Received: 2021-10-07 Accepted : 2022-08-03 Published : 2022-03-01

Keywords: CO2 emission, Green Closed-loop supply chain, Grasshopper Optimization Algorithm (GOA), Defective product, Mixed-integer programming,

Abstract :

This paper proposes a bi-objective model for a green closed-loop supply chain network design. Four levels for forward and five levels for reverse flow were considered, including plants, distribution centers, online retailers, traditional retailers and customers for forward flow and customers, collecting centers, disposal centers, repair centers and plants for the reverse flow. The objectives are minimizing the GHG emission and maximizing profit by considering defective products and a second market for these products. Also, online retailers were considered alongside with traditional ones, since the Covid-19 pandemic has led to increase in the amount of online shopping. GAMS software and the Lpmetric technique were used to solve the model in the small and medium sizes. However, for the large size, we used Grasshopper Optimization Algorithm (GOA) as a meta-heuristic approach since solving the large size problem with GAMS is a complicated and time-consuming process. We provided Numerical and computational results to prove the efficiency and feasibility of the presented model. Finally, the managerial insights and future works were provided.

References:

[1] Aghsami, A., Samimi, Y. and Aghaei, A., 2021. A
novel Markovian queueing-inventory model with
imperfect production and inspection processes: A
hospital case study. Computers & Industrial
Engineering, 162, p.107772.

[2] Agrawal, V. V., Ferguson, M., & Souza, G. C. (2016).
Trade-in rebates for price discrimination and product
recovery. IEEE Transactions on Engineering
Management, 63(3), 326-339.

[3] Aldoukhi, M., & Gupta, S. M. (2020). Use of Maximal
Covering Location Problem to Design a Closed Loop
Supply Chain Network Under Product Substitution.
In Applications of Management Science. Emerald
Publishing Limited.

[4] Amin, S. H., & Zhang, G. (2013). A multi-objective
facility location model for closed-loop supply chain
network under uncertain demand and return. Applied
Mathematical Modelling, 37(6), 4165-4176.

[5] Amin, S. H., Zhang, G., & Akhtar, P. (2017). Effects of
uncertainty on a tire closed-loop supply chain
network. Expert Systems with Applications, 73, 82-91.

[6] Anvari, S., & Turkay, M. (2017). The facility location
problem from the perspective of triple bottom line
accounting of sustainability. International Journal of
Production Research, 55(21), 6266-6287.

[7] Aryanezhad, M. B., Jabbarzadeh, A., & Zareei, A. (2009,
December). Combination of genetic algorithm and LPmetric to solve single machine bi-criteria scheduling
problem. In 2009 IEEE International Conference on
Industrial Engineering and Engineering Management
(pp. 1915-1919). IEEE.
[8] Aziziankohan, A., Jolai, F., Khalilzadeh, M., Soltani, R.,
& Tavakkoli-Moghaddam, R. (2017). Green supply
chain management using the queuing theory to handle
congestion and reduce energy consumption and
emissions from supply chain transportation
fleet. Journal of Industrial Engineering and
Management (JIEM), 10(2), 213-236.
[9] Bakhshi, A., & Heydari, J. (2021). An optimal put option
contract for a reverse supply chain: case of
remanufacturing capacity uncertainty. Annals of
Operations Research, 1-24.
[10]Balinski, M. L. (1965). Integer programming: methods,
uses, computations. Management science, Vol.12, No.
3, November 1965, pp. 253-313.
[11]Bieniek, M. (2015). A note on the facility location
problem with stochastic demands. Omega, 55, 53-60.
[12]Chakraborty, A., Maiti, T., & Giri, B. C. (2021).
Consignment stock policy in a closed-loop supply
chain. RAIRO-Operations Research, 55, S1913-S1934.
[13]Chauhan, D., Unnikrishnan, A., & Figliozzi, M. (2019).
Maximum coverage capacitated facility location
problem with range constrained drones. Transportation
Research Part C: Emerging Technologies, 99, 1-18.
[14]Danesh, M., Sandor, S., & Mosavi, A. (2020). Facility
Location Optimization Using a Hybrid Model of
Disassembly Line Balancing and Closed-Loop Supply
Chain (No. 2417). EasyChair.
[15] de Armas, J., Juan, A. A., Marquès, J. M., & Pedroso, J.
P. (2017). Solving the deterministic and stochastic
uncapacitated facility location problem: from a heuristic
to a simheuristic. Journal of the Operational Research
Society, 68(10), 1161-1176.
[16]De Giovanni, P., & Zaccour, G. (2014). A two-period
game of a closed-loop supply chain. EuropeanJournal
of Operational Research, 232(1), 22-40.
[17]Dehghan-Bonari, M., Bakhshi, A., Aghsami, A., &
Jolai, F. (2021). Green supply chain management
through call option contract and revenue-sharing
contract to cope with demand uncertainty. Cleaner
Logistics and Supply Chain, 2, 100010.
[18]Diabat, A., Abdallah, T. & Henschel, A. (2015). A
closed-loop location-inventory problem with spare parts
consideration. Computers & Operations Research. 54,
245-256.
[19]Fallah, H., Eskandari, H., & Pishvaee, M. S. (2015).
Competitive closed-loop supply chain network design
under uncertainty. Journal of Manufacturing
Systems, 37, 649-661.
[20]Fareeduddin, M., Hassan, A., Syed, M. N., & Selim, S.
Z. (2015). The impact of carbon policies on closed-loop
supply chain network design. Procedia CIRP, 26, 335-
340.
[21]Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M.
(2018). A stochastic multi-objective model for a closedloop supply chain with environmental
considerations. Applied Soft Computing, 69, 232-249.
[22]Ghadge, A., Yang, Q., Caldwell, N., König, C., &
Tiwari, M. K. (2016). Facility location for a closed-loop
distribution network: a hybrid approach. International
Journal of Retail & Distribution Management, 44(9),
884-902.
[23]Guide Jr, V. D. R., & Van Wassenhove, L. N. (2009).
OR FORUM—The evolution of closed-loop supply
chain research. Operations research, 57(1), 10-18.
[24]Guo, J.Q., Yu, H.L., Gen, M. (2020). Research on green
closed-loop supply chain with the consideration of
double subsidy in e-commerce environment. Computers
& Industrial Engineering, 149, doi:
10.1016/j.cie.2020.106779.
[25]Heydari, J., & Bakhshi, A. (2022). Contracts between an
e-retailer and a third party logistics provider to expand
home delivery capacity. Computers & Industrial
Engineering, 163, 107763.
[26]Isaloo, F., & Paydar, M. M. (2020). Optimizing a robust
bi-objective supply chain network considering
environmental aspects: a case study in plastic injection
industry. International Journal of Management Science
and Engineering Management, 15(1), 26-38.
[27]Jabbarzadeh, A., Haughton, M., & Khosrojerdi, A.
(2018). Closed-loop supply chain network design under
disruption risks: A robust approach with real world
application. Computers & industrial engineering, 116,
178-191.
[28]Jolai, F., Hashemi, P., Heydari, J., Bakhshi, A., &
Keramati, A. (2020). Optimizing a Reverse Logistics
System by Considering Quality of Returned Products.
Advances in Industrial Engineering, 54(2), 165-184.
[29]Karatas, M., & Yakıcı, E. (2018). An iterative solution
approach to a multi-objective facility location
problem. Applied Soft Computing, 62, 272-287.
[30]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. Computers & Operations Research, 65, 93-103.
[31]Li, J., Chu, F., Prins, C., & Zhu, Z. (2014). Lower and
upper bounds for a two-stage capacitated facility
location problem with handling costs. European
Journal of Operational Research, 236(3), 957-967.
[32]Liu, M., Liu, R., Zhu, Z., Chu, C., & Man, X. (2018). A
bi-objective green closed loop supply chain design
problem with uncertain demand. Sustainability, 10(4),
967.
[33]Liu, P., & Yi, S. P. (2017). Pricing policies of green
supply chain considering targeted advertising and
product green degree in the big data
environment. Journal of Cleaner Production, 164,
1614-1622.
[34]Mardan, E., Govindan, K., Mina, H., & GholamiZanjani, S. M. (2019). An accelerated benders
decomposition algorithm for a bi-objective green closed
loop supply chain network design problem. Journal of
Cleaner Production, 235, 1499-1514.
[35]Masoumi, M., Aghsami, A., Alipour-Vaezi, M., Jolai,
F. and Esmailifar, B., 2021. An M/M/C/K queueing
system in an inventory routing problem considering
congestion and response time for post-disaster
humanitarian relief: a case study. Journal of
Humanitarian Logistics and Supply Chain
Management.
[36]Min, H., & Kim, I. (2012). Green supply chain
research: past, present, and future. Logistics Research,
4(1), 39-47.
[37]Mohammed, F., Selim, S. Z., Hassan, A., & Syed, M.
N. (2017). Multi-period planning of closed-loop supply
chain with carbon policies under
uncertainty. Transportation Research Part D:
Transport and Environment, 51, 146-172.
[38]Mohtashami, Z., Aghsami, A., & Jolai, F. (2020). A
green closed loop supply chain design using queuing
system for reducing environmental impact and energy
consumption. Journal of cleaner production, 242,
118452.
[39]Momeni, B., Aghsami, A. and Rabbani, M., 2019.
Designing Humanitarian Relief Supply Chains by
Considering the Reliability of Route, Repair Groups
and Monitoring Route. Advances in Industrial
Engineering, 53(4), pp.93-126.
[40]Noh, J., & Kim, J. S. (2019). Cooperative green supply
chain management with greenhouse gas emissions and
fuzzy demand. Journal of Cleaner Production, 208,
1421-1435.
[41]Ortega, J., Tóth, J., Moslem, S., Péter, T., & Duleba, S.
(2020). An Integrated Approach of Analytic Hierarchy
Process and Triangular Fuzzy Sets for Analyzing the
Park-and-Ride Facility Location
Problem. Symmetry, 12(8), 1225.
[42]Pasandideh, S. H. R., Niaki, S. T. A., & Asadi, K.
(2015). Optimizing a bi-objective multi-product multiperiod three echelon supply chain network with
warehouse reliability. Expert Systems with
Applications, 42(5), 2615-2623.
[43]Peprah, J. A., Opoku-Fofie, I., & Nduro, K. (2016).
Factors influencing green supply chain in the mining
sector in Ghana. European Journal of Logistics,
Purchasing and Supply Chain Management, 4(1), 32-
50.
[44]Rezaei, A., Shahedi, T., Aghsami, A., Jolai, F., & Feili,
H. (2021). Optimizing a bi-objective locationallocation-inventory problem in a dual-channel supply
chain network with stochastic demands. RAIROOperations Research, 55(5), 3245-3279.
[45]Saremi, S., Mirjalili, S., & Lewis, A. (2017).
Grasshopper optimisation algorithm: theory and
application. Advances in Engineering Software, 105,
30-47.
[46]Serrano, A., Faulin, J., Astiz, P., Sánchez, M., &
Belloso, J. (2015). Locating and designing a biorefinery
supply chain under uncertainty in Navarre: a stochastic
facility location problem case. Transportation
Research Procedia, 10, 704-713.
[47]Shavarani, S. M., Nejad, M. G., Rismanchian, F., &
Izbirak, G. (2018). Application of hierarchical facility
location problem for optimization of a drone delivery
system: a case study of Amazon prime air in the city of
San Francisco. The International Journal of Advanced
Manufacturing Technology, 95(9), 3141-3153.
[48]Srivastava, S. K. (2007). Green supply‐chain
management: a state‐of‐the‐art literature review.
International journal of management reviews, 9(1), 53-
80.
[49]Stollsteimer, J. F. (1961). The effect of technical
change and output expansion on the optimum number,
size, and location of pear marketing facilities in a
California pear producing region. University of
California, Berkeley.
[50]Talaei, M., Moghaddam, B. F., Pishvaee, M. S.,
Bozorgi-Amiri, A., & Gholamnejad, S. (2016). A
robust fuzzy optimization model for carbon-efficient
closed-loop supply chain network design problem: a
numerical illustration in electronics industry. Journal of
cleaner production, 113, 662-673.
[51]Tavana, M., Tohidi, H., Alimohammadi, M., &
Lesansalmasi, R. (2021). A location-inventory-routing
model for green supply chains with low-carbon
emissions under uncertainty, Environmental Science
and Pollution Research, 28(36):50636-50648.
[52]Tohidi, H. (2015). Mathematical modeling of optimal
multi fuzzy locations of facilities based on the assumed
step distance among them in a convex set. Applied
Mathematical Modelling, 39, 7442-7451.
[53]Tumpa, T. J., Ali, S. M., Rahman, M. H., Paul, S. K.,
Chowdhury, P., & Khan, S. A. R. (2019). Barriers to
green supply chain management: An emerging
economy context. Journal of Cleaner Production, 236,
117617.
[54]Wu, G. H., Chang, C. K., & Hsu, L. M. (2018).
Comparisons of interactive fuzzy programming
approaches for closed-loop supply chain network
design under uncertainty. Computers & Industrial
Engineering, 125, 500-513.
[55]Yang, C., & Chen, X. (2020). A novel approach
integrating FANP and MOMILP for the collection
center location problem in closed-loop supply chain.
International Journal of Sustainable Engineering,
13(3), 171-183.
[56]Yavari, M., & Zaker, H. (2019). An integrated twolayer network model for designing a resilient greenclosed loop supply chain of perishable products under
disruption. Journal of Cleaner Production, 230, 198-
218.
[57]Zhen, L., Sun, Q., Wang, K., & Zhang, X. (2019).
Facility location and scale optimization in closed-loop
supply chain. International Journal of Production
Research, 57(24), 7567-7585.
[58]Zhao, X., Xia, X., Wang, L., & Yu, G. (2018). Riskaverse facility location for green closed-loop supply
chain networks design under uncertainty.
Sustainability, 10(11), 4072.
[59]Zhu, Q., Sarkis, J., & Lai, K. H. (2007). Initiatives and
outcomes of green supply chain management
implementation by Chinese manufacturers. Journal of
environmental management, 85(1), 179-189.