Optimization of vehicle routing problem with time windows for cold chain logistics based on carbon tax

Sustainability (Switzerland)

Volumn 9, Issue 5, 2017, Pages

  Wang, Songyi ^a   Tao, Fengming ^a   Shi, Yuhe ^b   Wen, Haolin ^c  

^a CHONGQING UNIVERSITY   (China)

^b SOUTHWEST JIAOTONG UNIVERSITY   (China)

^c NAVAL UNIVERSITY OF ENGINEERING   (China)

Author keywords

Carbon footprint; Carbon tax; Cold chain logistic distribution; Cycle evolutionary genetic algorithm; Vehicle routing problem

Indexed keywords

CARBON EMISSION; CARBON FOOTPRINT; ENVIRONMENTAL ECONOMICS; EXPERIMENTAL STUDY; GENETIC ALGORITHM; LOGISTICS; OPTIMIZATION; TRANSPORTATION PLANNING;

CHINA;

EID: 85019105048     PISSN: None     EISSN: 20711050     Source Type: Journal    
DOI: 10.3390/su9050694     Document Type: Article

References (44)

1. 2 Emissions Induced by Agricultural Inputs in China over 1991-2014. Sustainability 2016, 8, 414-426
2. Piecyk, M.I.; Mckinnon, A.C. Forecasting the carbon footprint of road freight transport in 2020. Int. J. Prod. Econ. 2010, 128, 31-42
3. Jingyuan, Z. Billions of carbon trading market is about to start. People's Dig. 2016, 22, 46-47
4. Dantzig, G.B.; Ramser, J.H. The Truck Dispatching Problem. Manag. Sci. 1959, 6, 80-91
5. Desrochers, M.; Verhoog, T.W. A new heuristic for the fleet size and mix vehicle routing problem. Comput. Oper. Res. 1991, 18, 263-274
6. Solomon, M.M.; Desrosiers, J. Time Window Constrained Routing and Scheduling Problems. Transp. Sci. 1988, 22, 1-13
7. Jabali, O.; Leus, R.; Van Woensel, T.; de Kok, T. Self-imposed time windows in vehicle routing problems. OR Spectr. 2015, 37, 331-352
8. Moghaddam, B.F.; Ruiz, R.; Sadjadi, S.J. Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm. Comput. Ind. Eng. 2012, 62, 306-317
9. Cattaruzza, D.; Absi, N.; Feillet, D. Vehicle routing problems with multiple trips. 4OR 2016, 14, 223-259
10. Laporte, G.; Mercure, H.; Nobert, Y. An exact algorithm for the asymmetrical capacitated vehicle routing problem. Networks 2006, 16, 33-46
11. Righini, G.; Salani, M. New dynamic programming algorithms for the resource constrained elementary shortest path problem. Networks 2005, 51, 155-170
12. Kallehauge, B. Formulations and exact algorithms for the vehicle routing problem with time windows. Comput. Oper. Res. 2008, 35, 2307-2330
13. Pichpibul, T.; Kawtummachai, R. An improved Clarke and Wright savings algorithm for the capacitated vehicle routing problem. ScienceAsia 2012, 38, 307-318
14. Yu, B.; Jin, P.H.; Yang, Z.Z. Two-stage heuristic algorithm for multi-depot vehicle routing problem with time windows. Syst. Eng. Theory Pract. 2012, 32, 1793-1800
15. Montané, F.A.T.; Galvão, R.D. A tabu search algorithm for the vehicle routing problem with simultaneous pick-up and delivery service. Comput. Oper. Res. 2009, 33, 595-619
16. Sbihi, A.; Eglese, R.W. Combinatorial optimization and Green Logistics. Ann. Oper. Res. 2010, 175, 159-175
17. Lin, J.; FU, P.; Li, X.; Zhang, J.; Zhu, D. Study on Vehicle Routing Problem and Tabu Search Algorithmunder Low-carbon Environment. Chin. J. Manag. Sci. 2015, 23, 98-106
18. Palmer, A. The Development of an Integrated Routing and Carbon Dioxide Emissions Model for Goods Vehicles. Ph.D. Thesis, Cranfield University, Cranfield, UK, 2007
19. Maden, W.; Eglese, R.; Black, D. Vehicle Routing and Scheduling with Time-Varying Data: A Case Study. J. Oper. Res. Soc. 2010, 61, 515-522
20. Kuo, Y. Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Comput. Ind. Eng. 2010, 59, 157-165
21. Ji, Y.; Yang, H.; Zhou, Y. In Vehicle Routing Problem with Simultaneous Delivery and Pickup for Cold-chain Logistics. In Proceedings of the International Conference on Modeling, Simulation and Applied Mathematics, Phuket, Thailand, 23-24 August 2015
22. Yapeng, Z.; Na, L. Research on Elite Selection Based Partheno-genetic Algorithm under Optimized Cold-chain Logistics VRP Model. Math. Pract. Theory 2016, 46, 87-96
23. Xiangguo, M.; Tongjuan, L.; Pingzhe, Y.; Rongfen, J. Vehicle Routing Optimization Model of Cold Chain Logistics Based on Stochastic Demand. J. Syst. Simul. 2016, 8, 1824-1832
24. Tarantilis, C.D.; Kiranoudis, C.T. Distribution of fresh meat. J. Food Eng. 2002, 51, 85-91
25. Amorim, P.; Parragh, S.N.; Sperandio, F.; Almada-Lobo, B. A rich vehicle routing problem dealing with perishable food: A case study. Top 2014, 22, 489-508
26. Liu, W.Y.; Lin, C.C.; Chiu, C.R.; Tsao, Y.S.;Wang, Q. Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths. Sustainability 2014, 6, 4658-4684
27. Li, X. Development of Cold Chain Logistics in China. In Contemporary Logistics in China: New Horizon and New Blueprint; Wang, L., Lee, S.-J., Chen, P., Jiang, X.-M., Liu, B.-L., Eds.; Springer: Singapore, 2016; pp. 263-288
28. Lakshmisha, I.P.; Ravishankar, C.N.; Ninan, G.; Mohan, C.O.; Gopal, T.K. Effect of freezing time on the quality of Indian mackerel (Rastrelliger kanagurta) during frozen storage. J. Food Sci. 2008, 73, 345-353
29. Jinlin, Z.; Jing, X. Review of research on energy conservation and emission reduction of refrigerated vehicle in China. Food Mach. 2013, 29, 236-239
30. Xiaoning, W. Vehicles' Distribution Route Research of Fresh Agricultural Products of Cold Chain Logistics under the Agricultural Super-Docking Mode; East China Jiaotong University: Nanchang, China, 2014
31. Duro, J.A. International mobility in carbon dioxide emissions. Energy Policy 2013, 55, 208-216
32. Schafer, A.; Victor, D.G. Global passenger travel: Implications for carbon dioxide emissions. Energy 1999, 24, 657-679
33. Srivastava, S.K. Green supply-chain management: A state-of-the-art literature review. Int. J. Manag. Rev. 2007, 9, 53-80
34. Liguo, Z.; Dong, L.; Dequn, Z. Dynamic Carbon Dioxide Emissions Performance and Regional Disparity of Logistics Industry in China-The Empirical Analysis Based on Provincial Panel Data. Syst. Eng. 2013, 4, 95-102
35. Ottmar, R.D.Wildland fire emissions, carbon, and climate: Modeling fuel consumption. For. Ecol. Manag. 2014, 317, 41-50
36. Xiao, Y.; Zhao, Q.; Kaku, I.; Xu, Y. Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Comput. Oper. Res. 2012, 39, 1419-1431
37. Xu, L.; Jia, W.; Ming, H. Application research on improved cyclical virus evdution genetic algorithm. Comput. Integr. Manuf. Syst. 2007, 13, 777-781
38. Bermudez, C.; Graglia, P.; Stark, N.; Salto, C.; Alfonso, H. Comparison of Recombination Operators in Panmictic and Cellular GAs to Solve a Vehicle Routing Problem. Iberoam. J. Intel. Artif. 2010, 14, 34-44
39. Haifeng, Y.; Xufa, W. Interactive Genetic Algorithm Based on Tournament Selection and Its Application. J. Chin. Comput. Syst. 2009, 30, 1824-1827
40. Andreica, A.; Chira, C. Best-order crossover for permutation-based evolutionary algorithms. Appl. Intell. 2015, 42, 751-776
41. Schwartz, Y.; Raslan, R.; Mumovic, D. Implementing multi objective genetic algorithm for life cycle carbon footprint and life cycle cost minimisation: A building refurbishment case study. Energy 2016, 97, 58-68
42. Neng, W.; Meixian, J.; Jiajing, F.A cycle evolutionary genetic algorithm for vehicle routing problem. Machinery 2012, 50, 25-28
43. Zhou, L.; Wang, X.; Ni, L.; Lin, Y. Location-Routing Problem with Simultaneous Home Delivery and Customer's Pickup for City Distribution of Online Shopping Purchases. Sustainability 2016, 8, 828
44. Mcausland, C.; Najjar, N. Carbon Footprint Taxes. Environ. Resour. Econ. 2015, 61, 37-70