Model of routing for raw milk collection using genetic algorithms

Authors

  • Ricardo Rosales Vásquez Universidad Autónoma de Occidente
  • Maritza Correa Valencia Universidad Autónoma de Occidente

DOI:

https://doi.org/10.18046/syt.v12i31.1916

Keywords:

Model of routing, metaheuristic methods, genetic algorithms.

Abstract

The article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genetic algorithm. The results show that the routes obtained with the implementation of the genetic algorithm are feasible in terms of time and visited nodes, demonstrating the potential of this tool. The costs obtained by this method differ from the current methods by about 3%, which is within the range reported in the literature.

Author Biographies

  • Ricardo Rosales Vásquez, Universidad Autónoma de Occidente
    Business administrator, master’s student of Integral Logistics at the Universidad Autónoma de Occidente (Cali, Colombia).
  • Maritza Correa Valencia, Universidad Autónoma de Occidente

    Ph.D. Industrial Engineer, Master in Information technologies applied to production and Doctor of Computer Sciences and Artificial intelligence. Full-time professor and researcher of the Operations and Computer Department at the Universidad Autónoma de Occidente (Cali, Colombia).

References

Alegre, J., Laguna, M., & Pacheco, J. (2007). Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts. European Journal of Operational Research, 179(3), 736-746.

Baker, B. M., & Ayechew, M.A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5) 787-800.

Berger, J., & Barkaoui, M. (2003). A new hybrid genetic algorithm for the capacitated vehicle routing problem. The Journal of the Operational Research Society, 54(12), 1254-1262.

Claassen, G. D. & Hendriks, T.B. (2007). An application of special ordered sets to a periodic milk collection problem. European Journal of Operational Research, 180(2), 754-769.

Coene, S., Arnout, A., & Spieksma, F. (2008). The periodic vehicle routing problem: a case study [working paper]. Retrieved from http://www.econ.kuleuven.be/public/n05012/

Duarte, A. (2007). Metaheurísticas. Madrid: Dykinson.
García-Najera, A. & Bullinaria, J. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287.

Hemmelmayr, V., Doerner, K.F., Hartl, R.F., & Savelsbergh, M.W. (2009). Delivery strategies for blood products supplies. OR spectrum, 31(4), 707-725.

Jozefowiez, N., Sernet, F., & Talbi, E.-G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.

Larrañaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13(2), 129-170.

Laudon, K.C., & Laudon, J.P. (2004). Sistemas de información gerencial: administración de la empresa digital. (trans. A. Núñez). México DF: Pearson.

Lei, H.-T. & Guo, B. (2010). Comments on "An improved model for vehicle routing problem with time constraint based on genetic algorithm”. Computers & Industrial Engineering, 59(3), 479-480.

Maroto, C., Alcaraz, J., & Ruiz, R. (2002). Investigación operativa: modelos y técnicas de optimización. Valencia: Universidad Politécnica de Valencia.

Nagata, Y., Bräysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737.

Oppen, J. & Lokketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213-3229.

Panapinun, K. & Charnsethikul, P. (2005). Vehicle routing and scheduling problems: A case study of food distribution in greater Bangkok [working paper]. Retrieved from
http://ieinter.eng.ku.ac.th/research/optimization/pan04a.pdf

Robusté, F. & Galván, D. (2005). e-logistics. Barcelona: Universidad Politécnica de Catalunya.

Sigurd, M., Pisinger, D., & Sig, M. (2004). Scheduling transportation of live animals. Transportation Science, 38(2), 197-209.

Sterzik, S. & Kopfer, H. (2013). A tabu search heuristic for the inland container transportation problem. Computers and Operations Research, 40(4), 953-962.

Tarantilis, C. D., & Kiranoudis, C. T. (2005). Operational research and food logistics. Journal of Food Engineering, 70(3), 253-255.

Vansteenwegen, P., Souffriau, W., & Sörensen, K. (2010). Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated ARC routing with soft time windows. Computers and Operations Research, 37(11), 1870-1876.

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Published

2014-12-23

Issue

Section

Case Report