Artya Lathifah, Sinta Rahmawidya Sulistyo, Izzawi Winda Murti, A.A.N Perwira Redi


Transportation and distribution are two things that are closely related to logistics problems However, on the other hand this activity can sometimes damage the environment. Emissions from fuels used in transportation and distribution activities accounted for 29.4% of the total costs incurred by the organization in their activities. From this issue many organizations finally make environmentally friendly logistics as priority in their activities, where the goal of minimizing distribution costs and maintaining sustainability of environments. Some factors that can be improved are: determination of the location depot, combination of vehicle and the route. Therefore, this study aims to develop mathematical model that optimize these three factors integration to minimize the emission cost. The results of this research are the mathematical model, optimization of the development of the Simulated Annealing (SA) method that is applied to the problem is able to get a reduction in total emissions costs up to 18.8%.


environmentally friendly logistics, facility location, emissions cost, optimization, multi-capacity vehicles and routes

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L. Ping, L. Strategy of Green Logistics and Sustainable Development, International Conference on Information Management, Innovation Management and Industrial Engineering. IEEE Computer Society (2009), pp.339-342.

Y.-y. Tseng, W.L. Yue, M.A.Taylor. The role of transportation in logistics chain. Eastern Asia Society for Transportation Studies, 5 (2005), pp. 1657 - 1672.

D.J Forkenbrock. Comparison of external costs of rail and truck freight transportation. Transportation Research Part A: Policy and Practice, 35 (2001), pp. 321-337

H. Ohnishi, H. Greenhouse Gas Reduction Strategies in the Transport Sector: Preliminary Report. Tech. rep., OECD/ITF Joint Transport Research Centre Working Group on GHG Reduction Strategies in the Transport Sector, OECD/ITF, Paris (2012). < >(accessed 11.02. 17).

H.R. Kirby, B. Hutton, R.W. McQuaid, R. Raeside, X. Zhang. Modelling the effects of transport policy levers on fuel efficiency and national fuel consumption. Transportation Research Part D: Transport and Environment, 5 (2000), pp. 265-282.

E. Demir, T. Bektaş, T, and G. Laporte. An adaptive large neighborhood search heuristic for the Pollution-Routing Problem. European Journal of Operational Research, 223 (2012), pp. 346-359.

T. Bektas, and G.Laporte. The Pollution-Routing Problem. Transportation Research Part B-Methodological, Vol. 45 (2011), pp. 1232-1250.

E. Demir, T. Bektaş, T., G. Laporte. An adaptive large neighborhood search heuristic for the Pollution-Routing Problem. European Journal of Operational Research, 223 (2012), pp. 346-359.

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

Ç. Koç, T. Bektaş, O. Jabali, and G. Laporte, G. The fleet size and mix pollution-routing problem. Transportation Research Part B: Methodological, 70 (2014), pp. 239-254.

M.E.Toro, J.F. Franco, M.G. Echeveri, and F.G. Guimarães. A Multi-Objective Model for the Green capacitated Location-Routing Problem Considering Environmental Impact. Computers and Industrial Engineering 110 (2017), pp. 114-125

Gendreau, M., Potvin, J.-Y., 2010. Handbook of metaheuristics. Springer.

Yu, V.F., Redi, A.A.N.P., Jewpanya, P., Lathifah, S., Maghfiroh, M., Masruroh, NA. 2018. A simulated annealing heuristic for the Heterogeneous Fleet Pollution Routing Problem. Environmental Sustainability in Asian Logistics and Supply Chains, Springer, pp. 171-204. (accessed 11.14. 18)


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