Modelo de roteamento para coleta de leite cru utilizando algoritmos genéticos

Autores

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

DOI:

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

Palavras-chave:

Modelo de roteamento, métodos meta heurísticos, algoritmos genéticos.

Resumo

O artigo mostra o uso de um método meta heurístico - algoritmos genéticos - para avaliar um padrão de rotas de coleta de leite cru. Foi implementado um modelo baseado em dados reais, coletados por meio de trabalho de campo, seguindo o método do "Problema do Caixeiro Viajante", usando os algoritmos genéticos da caixa de ferramentas Matlab®. Os resultados mostram que as rotas obtidas com a implementação do algoritmo genético são viáveis em termos de tempo e de nós visitados, demonstrando assim o potencial desta ferramenta. Os custos obtidos por este método diferem dos atuais em aproximadamente 3%, o que está dentro do intervalo referido na literatura.

Biografia do Autor

  • 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).

Referências

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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Publicado

2014-12-23

Edição

Seção

Case Report