Green distribution center model: environmentally friendly and operational efficiency using a process approach and a taboo search metaheuristics
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Jul 16, 2015
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Jun 1, 2005
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Abstract
This article is intended to develop and validate a green distribution center model consisting of three components: a management module; a warehouse management system (WMS); and a metaheuristics. As a result of the validation of the model at a Distribution Center of a medium-size food company, a reduction of CO2 emissions was achieved, equivalent to 731 kg/month or 37% of issues for preparation of orders. Additionally, the modeling of a Taboo Search metaheuristics was developed to resolve the routing problem for the preparation of orders; this allowed increasing the operation efficiency in about 18.83% and to obtain a reduction of 198 kg of equivalent CO2 per month. Therefore, the green distribution center model, simultaneously, increased the efficiency and reduced the amount of kilograms of CO2, using an approach that had not been addressed in literature for this logistic process.
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Gomez Montoya, R. A., Correa Espinal, A. A., & Hernandez Vahos, J. D. (2005). Green distribution center model: environmentally friendly and operational efficiency using a process approach and a taboo search metaheuristics. Revista Ingenierías Universidad De Medellín, 16(31), 199–217. https://doi.org/10.22395/rium.v16n31a10
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References
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[3] J. J. Bartholdi and S. T. Hackman, Warehouse & Distribution Science: Release 0.96. The Supply Chain and Logistics Institute, 2014.
[4] A. Correa, R. Gómez and J. Cano, 'Gestión de almacenes y tecnologías de la información y comunicación (TIC),' Estudios Gerenciales, vol. 26, n.° 117, pp. 145–171, 2010.
[5] S. Henn and V. Schmid, 'Metaheuristics for order batching and sequencing in manual order picking systems,' Computers & Industrial Engineering, vol. 66, n.° 2, pp. 338–351, Oct. 2013.
[6] H. Min, 'Application of a decision support system to strategic warehousing decisions,' International Journal of Physical Distribution & Logistics Management, vol. 39, n.° 4, pp. 270-281, 2009.
[7] S. Henn, 'Metaheuristics for the order batching problem in manual order picking systems,' BuR Business Research Journal, vol. 3, n.° 1, pp. 1-24, 2010.
[8] O. Kulak, Y. Sahin, and M. E. Taner, 'Joint order batching and picker routing in single and multiple-cross-aisle warehouses using cluster-based tabu search algorithms,' Flex Serv Manuf J, vol. 24, n.° 1, pp. 52-80, Mar. 2012.
[9] M. de Brito and R. Dekker, 'Reverse logistics - a framework,' Econometric Institute Research Papers, vol. 1, pp. 1-19, Oct. 2002.
[10] S. Ubeda, F. J. Arcelus, and J. Faulin, 'Green logistics at Eroski: A case study,' International Journal of Production Economics, vol. 131, n.° 1, pp. 44-51, May 2011.
[11] R. Dekker, J. Bloemhof, and I. Mallidis, 'Operations Research for green logistics – An overview of aspects, issues, contributions and challenges,' European Journal of Operational Research, vol. 219, n.° 3, pp. 671-679, Jun. 2012.
[12] U. Martinsen and M. Björklund, 'Matches and gaps in the green logistics market,' Int Jnl Phys Dist & Log Manage, vol. 42, n.° 6, pp. 562-583, Jul. 2012.
[13] G. Zhang and Z. Zhao, 'Green Packaging Management of Logistics Enterprises,' Physics Procedia, vol. 24, Part B, pp. 900-905, 2012.
[14 ] Y. Y. Zhao and Y. J. Gu, 'Green Logistics and Social Sustainable Development,' in Advanced Materials Research, 2014, vol. 962, pp. 2180-2184.
[15 ] I. Harris, C. L. Mumford, and M. M. Naim, 'A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling,' Transportation Research Part E: Logistics and Transportation Review, vol. 66, pp. 1-22, Jun. 2014.
[16] S. Zhang, C. K. M. Lee, H. K. Chan, K. L. Choy, and Z. Wu, 'Swarm intelligence applied in green logistics: A literature review,' Engineering Applications of Artificial Intelligence, vol. 37, pp. 154-169, Jan. 2015.
[17] K. Lai and C. W. Y. Wong, 'Green logistics management and performance: Some empirical evidence from Chinese manufacturing exporters,' Omega, vol. 40, n.° 3, pp. 267-282, Jun. 2012.
[18] M. S. Pishvaee, S. A. Torabi, and J. Razmi, 'Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty,' Computers & Industrial Engineering, vol. 62, n.° 2, pp. 624-632, Mar. 2012.
[19] K. Dobers, A. Klukas, W. Lammers, M. Laux, G. Mauer, and M. Schneider, 'Green Logistics: Optimisation Approaches for Resource-Efficient Logistics Services,' in Efficiency and Logistics, U. Clausen, M. ten Hompel, and M. Klumpp, Eds. Springer Berlin Heidelberg, 2013, pp. 149-161.
[20] G. Ćirović, D. PamuÄar, and D. Božanić, 'Green logistic vehicle routing problem: Routing light delivery vehicles in urban areas using a neuro-fuzzy model,' Expert Systems with Applications, vol. 41, n.° 9, pp. 4245-4258, Jul. 2014.