A Multiple Objective Model for Vehicle Routing Problem with Time Windows: A Case Study

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Green transportation has emerged as an efficient way to promote a sustainable supply chain. Transportation activities have significant impact on the whole supply chain at any decision levels. At an operational level, vehicle routing decisions are one of the most critical determinants of the release of transportation emissions. Therefore, this study develops a mathematical model, with an aim to construct routes that simultaneously minimize total cost and total CO2 emissions from the transportation activities of a case study located in Can Tho City, Vietnam. A multiple-objective model with the consideration of different vehicle loading capacity, and time windows is then solved using a Weighted Tchebycheff method. Results show that route selection has a positive contribution toward a better balance between economic and environmental objectives.

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588-596

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March 2019

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© 2019 Trans Tech Publications Ltd. All Rights Reserved

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[1] Dekker, R., J. Bloemhof, and I. Mallidis, Operations Research for green logistics – An overview of aspects, issues, contributions and challenges. European Journal of Operational Research, 2012. 219(3): pp.671-679.

DOI: 10.1016/j.ejor.2011.11.010

Google Scholar

[2] EEA, EEE Greenhouse Gas Data (2008). (2011).

Google Scholar

[3] Dantzig, G.B. and J.H. Ramser, The Truck Dispatching Problem. Management Science, 1959. 6(1): pp.80-91.

DOI: 10.1287/mnsc.6.1.80

Google Scholar

[4] Kara, I., B. Kara, and M. Yetis, Energy Minimizing Vehicle Routing Problem. Vol. 4616. 2007. 62-71.

DOI: 10.1007/978-3-540-73556-4_9

Google Scholar

[5] Xiao, Y., et al., Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Computers & Operations Research, 2012. 39(7): pp.1419-1431.

DOI: 10.1016/j.cor.2011.08.013

Google Scholar

[6] Tavares, G., et al., A case study of fuel savings through optimisation of MSW transportation routes. Vol. 19. 2008. 444-454.

DOI: 10.1108/14777830810878632

Google Scholar

[7] Erdoğan, S. and E. Miller-Hooks, A Green Vehicle Routing Problem. Transportation Research Part E: Logistics and Transportation Review, 2012. 48(1): pp.100-114.

DOI: 10.1016/j.tre.2011.08.001

Google Scholar

[8] Fuel economy guide. US Department of Energy (2008).

Google Scholar

[9] Ubeda, S., F.J. Arcelus, and J. Faulin, Green logistics at Eroski: A case study. International Journal of Production Economics, 2011. 131(1): pp.44-51.

DOI: 10.1016/j.ijpe.2010.04.041

Google Scholar

[10] Kuo, Y., Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Vol. 59. 2010. 157-165.

DOI: 10.1016/j.cie.2010.03.012

Google Scholar

[11] Koç, Ç., et al., The fleet size and mix pollution-routing problem. Transportation Research Part B: Methodological, 2014. 70: pp.239-254.

DOI: 10.1016/j.trb.2014.09.008

Google Scholar

[12] Kwon, Y.-J., Y.-J. Choi, and D.-H. Lee, Heterogeneous fixed fleet vehicle routing considering carbon emission. Transportation Research Part D: Transport and Environment, 2013. 23: pp.81-89.

DOI: 10.1016/j.trd.2013.04.001

Google Scholar

[13] Kopfer, H. and H. Kopfer, Emissions minimization vehicle routing problem in dependence of different vehicle classes. 2013. 49-58.

DOI: 10.1007/978-3-642-35966-8_4

Google Scholar

[14] Racero, J., Environmental issues in vehicle routing problems. 2013. 215-241.

Google Scholar

[15] DEFRA, Guidelines to Defra's GHG Conversion Factors: Methodology Paper for Transport Emission Factors. Technical Report, Department of Environment, Food and Rural Affairs, (2008).

Google Scholar

[16] Waygood, E.O.D., T. Chatterton, and E. Avineri, Comparing and presenting city-level transportation CO2 emissions using GIS. Transportation Research Part D: Transport and Environment, 2013. 24: pp.127-134.

DOI: 10.1016/j.trd.2013.06.006

Google Scholar

[17] Wikipedia, (2017).

Google Scholar

[18] E. Steuer, R. and E. Choo, An Interactive Weighted Tchebycheff Procedure for Multiple Objective Programming. Vol. 26. 1983. 326-344.

DOI: 10.1007/bf02591870

Google Scholar