Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty

Transportation Research Part E: Logistics and Transportation Review

Volumn 89, Issue , 2016, Pages 182-214

  Zhalechian, M ^a   Tavakkoli Moghaddam, R ^a,b   Zahiri, B ^c   Mohammadi, M ^d  

^a UNIVERSITY OF TEHRAN   (Iran)

^b Universal Scientific Education and Research Network   (Iran)

^c 160 Jacobs Management Center   (United States)

^d ECOLE DES MINES DE SAINT ETIENNE   (France)

Author keywords

Closed loop supply chain; Inventory; Meta heuristic; Queuing theory; Routing; Sustainability

Indexed keywords

ALGORITHM; HEURISTICS; LOCATION THEORY; NETWORK ANALYSIS; ROUTING; STOCHASTICITY; SUPPLY CHAIN MANAGEMENT;

EID: 84962028746     PISSN: 13665545     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tre.2016.02.011     Document Type: Article

References (102)

1. Abdallah T., Diabat A., Simchi-Levi D. Sustainable supply chain design: a closed-loop formulation and sensitivity analysis. Product. Plann. Control 2012, 23:120-133.
2. Ahmadi-Javid A., Seddighi A.H. A location-routing problem with disruption risk. Transport. Res. Part E: Logist. Transport. Rev. 2013, 53:63-82.
3. Annamdas K.K., Rao S.S. Multi-objective optimization of engineering systems using game theory and particle swarm optimization. Eng. Optim. 2009, 41:737-752.
4. Asl-Najafi J., Zahiri B., Bozorgi-Amiri A., Taheri-Moghaddam A. A dynamic closed-loop location-inventory problem under disruption risk. Comput. Indust. Eng. 2015, 90:414-428.
5. Azadeh A., Rezaei-Malek M., Evazabadian F., Sheikhalishahi M. Improved design of CMS by considering operators decision-making styles. Int. J. Product. Res. 2015, 53.
6. Bacchetti A., Saccani N. Spare parts classification and demand forecasting for stock control: investigating the gap between research and practice. Omega 2012, 40:722-737.
7. Baker B.M., Ayechew M. A genetic algorithm for the vehicle routing problem. Comput. Oper. Res. 2003, 30:787-800.
8. Baumol W.J., Wolfe P. A warehouse-location problem. Oper. Res. 1958, 6:252-263.
9. Bazaraa M.S., Sherali H.D., Shetty C.M. Nonlinear Programming: Theory and Algorithms 2013, John Wiley & Sons.
10. Bektaş T., Laporte G. The pollution-routing problem. Transport. Res. Part B: Methodol. 2011, 45:1232-1250.
11. Brandenburg M., Govindan K., Sarkis J., Seuring S. Quantitative models for sustainable supply chain management: developments and directions. Eur. J. Oper. Res. 2014, 233:299-312.
12. Chaabane A., Ramudhin A., Paquet M. Designing supply chains with sustainability considerations. Product. Plann. Control 2011, 22:727-741.
13. Chaabane A., Ramudhin A., Paquet M. Design of sustainable supply chains under the emission trading scheme. Int. J. Product. Econ. 2012, 135:37-49.
14. Chatfield D.C., Pritchard A.M. Returns and the bullwhip effect. Transport. Res. Part E: Logist. Transport. Rev. 2013, 49:159-175.
15. Chung C.-J., Wee H.-M. Short life-cycle deteriorating product remanufacturing in a green supply chain inventory control system. Int. J. Product. Econ. 2011, 129:195-203.
16. Chung S.-L., Wee H.-M., Yang P.-C. Optimal policy for a closed-loop supply chain inventory system with remanufacturing. Math. Comput. Modell. 2008, 48:867-881.
17. Črepinšek M., Liu S.-H., Mernik M. Exploration and exploitation in evolutionary algorithms: a survey. ACM Comput. Surveys (CSUR) 2013, 45:35.
18. Dai Z., Zheng X. Design of close-loop supply chain network under uncertainty using hybrid genetic algorithm: a fuzzy and chance-constrained programming model. Comput. Indust. Eng. 2015.
19. Daskin M.S., Coullard C.R., Shen Z.-J.M. An inventory-location model: Formulation, solution algorithm and computational results. Ann. Oper. Res. 2002, 110:83-106.
20. Dehghanian F., Mansour S. Designing sustainable recovery network of end-of-life products using genetic algorithm. Resourc. Conservat. Recycling 2009, 53:559-570.
21. Dekker R., Bloemhof J., Mallidis I. Operations research for green logistics-an overview of aspects, issues, contributions and challenges. Eur. J. Oper. Res. 2012, 219:671-679.
22. Derbel H., Jarboui B., Hanafi S., Chabchoub H. Genetic algorithm with iterated local search for solving a location-routing problem. Expert Syst. Appl. 2012, 39:2865-2871.
23. Devika K., Jafarian A., Nourbakhsh V. Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques. Eur. J. Oper. Res. 2014, 235:594-615.
24. Diabat A., Al-Salem M. An integrated supply chain problem with environmental considerations. Int. J. Product. Econ. 2015, 164:330-338.
25. Diabat A., Richard J.-P., Codrington C.W. A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design. Ann. Oper. Res. 2013, 203:55-80.
26. Diabat A., Abdallah T., Henschel A. A closed-loop location-inventory problem with spare parts consideration. Comput. Oper. Res. 2015, 54:245-256.
27. Elhedhli S., Merrick R. Green supply chain network design to reduce carbon emissions. Transport. Res. Part D: Transport Environ. 2012, 17:370-379.
28. Erdoğan S., Miller-Hooks E. A green vehicle routing problem. Transport. Res. Part E: Logist. Transport. Rev. 2012, 48:100-114.
29. Escobar J.W., Linfati R., Toth P. A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Comput. Oper. Res. 2013, 40:70-79.
30. Eskandarpour M., Dejax P., Miemczyk J., Péton O. Sustainable supply chain network design: an optimization-oriented review. Omega 2015, 54:11-32.
31. 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. J. Cleaner Product. 2013, 59:210-225.
32. Fahimnia B., Sarkis J., Eshragh A. A tradeoff model for green supply chain planning: a leanness-versus-greenness analysis. Omega 2015, 54:173-190.
33. Fahimnia B., Sarkis J., Davarzani H. Green supply chain management: a review and bibliometric analysis. Int. J. Product. Econ. 2015, 162:101-114.
34. Fallah H., Eskandari H., Pishvaee M.S. Competitive closed-loop supply chain network design under uncertainty. J. Manuf. Syst. 2015.
35. Fleischmann M., Minner S. Inventory management in closed loop supply chains. Supply Chain Management and Reverse Logistics 2004, 115-138. Springer.
36. Freling R., Romeijn H.E., Morales D.R., Wagelmans A.P. A branch-and-price algorithm for the multiperiod single-sourcing problem. Oper. Res. 2003, 51:922-939.
37. Georgiadis P. An integrated system dynamics model for strategic capacity planning in closed-loop recycling networks: a dynamic analysis for the paper industry. Simul. Modell. Pract. Theory 2013, 32:116-137.
38. Govindan K., Jafarian A., Khodaverdi R., Devika K. Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food. Int. J. Prod. Econ. 2014, 152:9-28.
39. Govindan K., Soleimani H., Kannan D. Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future. Eur. J. Oper. Res. 2015, 240:603-626.
40. Govindan K., Jafarian A., Nourbakhsh V. Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic. Comput. Oper. Res. 2015.
41. Gross D. Fundamentals of Queueing Theory 2008, John Wiley & Sons.
42. Gzara F., Nematollahi E., Dasci A. Linear location-inventory models for service parts logistics network design. Comput. Indust. Eng. 2014, 69:53-63.
43. Hasani A., Zegordi S.H., Nikbakhsh E. Robust closed-loop global supply chain network design under uncertainty: the case of the medical device industry. Int. J. Product. Res. 2015, 53:1596-1624.
44. Ho W., Ho G.T., Ji P., Lau H.C. A hybrid genetic algorithm for the multi-depot vehicle routing problem. Eng. Appl. Artif. Intell. 2008, 21:548-557.
45. Javid A.A., Azad N. Incorporating location, routing and inventory decisions in supply chain network design. Transport. Res. Part E: Logist. Transport. Rev. 2010, 46:582-597.
46. Jiménez M., Arenas M., Bilbao A., Rodri M.V. Linear programming with fuzzy parameters: an interactive method resolution. Eur. J. Oper. Res. 2007, 177:1599-1609.
47. Kaya O., Urek B. A mixed integer nonlinear programming model and heuristic solutions for location, inventory and pricing decisions in a closed loop supply chain. Comput. Oper. Res. 2016, 65:93-103.
48. Koudal P. The service revolution in global manufacturing industries. Deloitte Res. 2006, 2.
49. Kumar R.S., Kondapaneni K., Dixit V., Goswami A., Thakur L., Tiwari M. Multi-objective modeling of production and pollution routing problem with time window: a self-learning particle swarm optimization approach. Comput. Indust. Eng. 2015.
50. Lakin, N., Scheubel, V., 2010. Corporate community involvement. The Definite Guide to Maximizing Your Business' Societal Engagement.
51. Li H., Womer N.K. Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming. Eur. J. Oper. Res. 2015.
52. Lieckens K., Vandaele N. Reverse logistics network design with stochastic lead times. Comput. Oper. Res. 2007, 34:395-416.
53. Liu S., Lee S. A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration. Int. J. Adv. Manuf. Technol. 2003, 22:941-950.
54. Liu S., Lin C. A heuristic method for the combined location routing and inventory problem. Int. J. Adv. Manuf. Technol. 2005, 26:372-381.
55. Liu L., Huang G., Liu Y., Fuller G., Zeng G. A fuzzy-stochastic robust programming model for regional air quality management under uncertainty. Eng. Optim. 2003, 35:177-199.
56. Melo M.T., Nickel S., Saldanha-da-Gama F. Facility location and supply chain management-a review. Eur. J. Oper. Res. 2009, 196:401-412.
57. Miranda P.A., Garrido R.A. A simultaneous inventory control and facility location model with stochastic capacity constraints. Netw. Spatial Econ. 2006, 6:39-53.
58. Mohammadi, M., Tavakkoli-Moghaddam, R., 2015. Design of a fuzzy bi-objective reliable p-hub center problem. J. Intell. Fuzzy Syst., pp. 1-18, (Preprint).
59. Mohammadi M., Jolai F., Tavakkoli-Moghaddam R. Solving a new stochastic multi-mode p-hub covering location problem considering risk by a novel multi-objective algorithm. Appl. Math. Modell. 2013, 37:10053-10073.
60. Mohammadi M., Torabi S., Tavakkoli-Moghaddam R. Sustainable hub location under mixed uncertainty. Transport. Res. Part E: Logist. Transport. Rev. 2014, 62:89-115.
61. Mohammadi M., Dehbari S., Vahdani B. Design of a bi-objective reliable healthcare network with finite capacity queue under service covering uncertainty. Transport. Res. Part E: Logist. Transport. Rev. 2014, 72:15-41.
62. Mohammadi M., Siadat A., Dantan JY., Tavakkoli-Moghaddam R. Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods. Int. J. Product. Res. 2015, 53(7):2202-2224.
63. Mohammadi M., Tavakkoli-Moghaddam R., Siadat A., Rahimi Y. A game-based meta-heuristic for a fuzzy bi-objective reliable hub location problem. Eng. Appl. Artif. Intell. 2016, 50:1-19.
64. Mohammadi M., Tavakkoli-Moghaddam R., Siadat A., Dantan JY. Design of a reliable logistics network with hub disruptions under uncertainty. Appl. Math. Modell. 2016, 10.1016/j.apm.2016.01.011.
65. Moin N.H., Salhi S., Aziz N. An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem. Int. J. Product. Econ. 2011, 133:334-343.
66. Montgomery D.C., Runger G.C., Hubele N.F. Engineering Statistics 2009, John Wiley & Sons.
67. Mota B., Gomes M.I., Carvalho A., Barbosa-Povoa A.P. Towards supply chain sustainability: economic, environmental and social design and planning. J. Cleaner Product. 2014.
68. Mousavi S.M., Vahdani B., Tavakkoli-Moghaddam R., Hashemi H. Location of cross-docking centers and vehicle routing scheduling under uncertainty: a fuzzy possibilistic-stochastic programming model. Appl. Math. Modell. 2014, 38:2249-2264.
69. Mousazadeh M., Torabi S.A., Pishvaee M.S. Green and reverse logistics management under fuzziness. Supply Chain Management Under Fuzziness 2014, 607-637. Springer.
70. Mousazadeh M., Torabi S., Zahiri B. A robust possibilistic programming approach for pharmaceutical supply chain network design. Comput. Chem. Eng. 2015, 82:115-128.
71. Nagy G., Salhi S. Location-routing: issues, models and methods. Eur. J. Oper. Res. 2007, 177:649-672.
72. Nekooghadirli N., Tavakkoli-Moghaddam R., Ghezavati V., Javanmard S. Solving a new bi-objective location-routing-inventory problem in a distribution network by meta-heuristics. Comput. Indust. Eng. 2014, 76:204-221.
73. Niakan F., Vahdani B., Mohammadi M. A multi-objective optimization model for hub network design under uncertainty: an inexact rough-interval fuzzy approach. Eng. Optim. 2015, 47(12):1670-1688.
74. Nozick L.K., Turnquist M.A. Inventory, transportation, service quality and the location of distribution centers. Eur. J. Oper. Res. 2001, 129:362-371.
75. Pagell M., Wu Z. Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. J. Supply Chain Manage. 2009, 45:37-56.
76. Pan S., Ballot E., Fontane F. The reduction of greenhouse gas emissions from freight transport by pooling supply chains. Int. J. Product. Econ. 2013, 143:86-94.
77. Pishvaee M., Razmi J., Torabi S.A. Robust possibilistic programming for socially responsible supply chain network design: a new approach. Fuzzy Sets Syst. 2012, 206:1-20.
78. Pishvaee M., Razmi J., Torabi S. An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: a case study of medical needle and syringe supply chain. Transport. Res. Part E: Logist. Transport. Rev. 2014, 67:14-38.
79. Potvin J.-Y., Bengio S. The vehicle routing problem with time windows part II: genetic search. INFORMS J. Comput. 1996, 8:165-172.
80. Prins C., Prodhon C., Calvo R.W. Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. 4OR 2006, 4:221-238.
81. Prodhon C., Prins C. A survey of recent research on location-routing problems. Eur. J. Oper. Res. 2014, 238:1-17.
82. Rahimi Y., Tavakkoli-Moghaddam R., Mohammadi M., Sadeghi M. Multi-objective hub network design under uncertainty considering congestion: an M/M/c/K queue system. Appl. Math. Modell. 2015, 10.1016/j.apm.2015.11.019.
83. Ramezani M., Bashiri M., Tavakkoli-Moghaddam R. A robust design for a closed-loop supply chain network under an uncertain environment. Int. J. Adv. Manuf. Technol. 2013, 66:825-843.
84. Rezaee A., Dehghanian F., Fahimnia B., Beamon B. Green supply chain network design with stochastic demand and carbon price. Ann. Oper. Res. 2015, 1-23.
85. Rezaei-Malek M., Tavakkoli-Moghaddam R. Robust humanitarian relief logistics network planning. Uncertain Supply Chain Manage. 2014, 2:73-96.
86. Saeedi S., Mohammadi M., Torabi S. A De Novo programming approach for a robust closed-loop supply chain network design under uncertainty: an M/M/1 queueing model. Int. J. Indust. Eng. Comput. 2015, 6:211-228.
87. Sedighy S.Q., Rezaei-Malek M. A novel multi-objective mathematical model for planning an auxiliary public transportation network: a covering-routing approach. Econ. Comput. Econ. Cybernet. Stud. Res. 2015, 49.
88. Shen Z.-J.M., Coullard C., Daskin M.S. A joint location-inventory model. Transport. Sci. 2003, 37:40-55.
89. Shu J., Teo C.-P., Shen Z.-J.M. Stochastic transportation-inventory network design problem. Oper. Res. 2005, 53:48-60.
90. Sivanandam S., Deepa S. Introduction to Genetic Algorithms 2008, Springer Publishing Company, Incorporated.
91. Snyder L.V. Facility location under uncertainty: a review. IIE Trans. 2006, 38:547-564.
92. Suzuki Y. A new truck-routing approach for reducing fuel consumption and pollutants emission. Transport. Res. Part D: Transport Environ. 2011, 16:73-77.
93. Tajik N., Tavakkoli-Moghaddam R., Vahdani B., Mousavi S.M. A robust optimization approach for pollution routing problem with pickup and delivery under uncertainty. J. Manuf. Syst. 2014, 33:277-286.
94. Tasan A.S., Gen M. A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries. Comput. Indust. Eng. 2012, 62:755-761.
95. Vahdani B., Mohammadi M. A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system. Int. J. Product. Econ. 2015, 170:67-87.
96. Vahdani B., Tavakkoli-Moghaddam R., Modarres M., Baboli A. Reliable design of a forward/reverse logistics network under uncertainty: a robust-M/M/c queuing model. Transport. Res. Part E: Logist. Transport. Rev. 2012, 48:1152-1168.
97. Wang F., Lai X., Shi N. A multi-objective optimization for green supply chain network design. Decis. Support Syst. 2011, 51:262-269.
98. Watson-Gandy C., Dohrn P. Depot location with van salesmen-a practical approach. Omega 1973, 1:321-329.
99. Wee H.-M., Lee M.-C., Jonas C., Wang C.E. Optimal replenishment policy for a deteriorating green product: life cycle costing analysis. Int. J. Product. Econ. 2011, 133:603-611.
100. Wen Y., Xu H., Yang J. A heuristic-based hybrid genetic-variable neighborhood search algorithm for task scheduling in heterogeneous multiprocessor system. Inform. Sci. 2011, 181:567-581.
101. Zahiri B., Tavakkoli-Moghaddam R., Pishvaee M.S. A robust possibilistic programming approach to multi-period location-allocation of organ transplant centers under uncertainty. Comput. Indust. Eng. 2014, 74:139-148.
102. Zahiri B., Tavakkoli-Moghaddam R., Mohammadi M., Jula P. Multi-objective design of an organ transplant network under uncertainty. Transport. Res. Part E: Logist. Transport. Rev. 2014, 72:101-124.