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A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands

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Learning and Intelligent Optimization (LION 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8426))

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Abstract

The Clonal Selection Algorithm is the most known algorithm inspired from the Artificial Immune Systems and used effectively in optimization problems. In this paper, this nature inspired algorithm is used in a hybrid scheme with other metaheuristic algorithms for successfully solving the Vehicle Routing Problem with Stochastic Demands (VRPSD). More precisely, for the solution of this problem, the Hybrid Clonal Selection Algorithm (HCSA) is proposed which combines a Clonal Selection Algorithm (CSA), a Variable Neighborhood Search (VNS), and an Iterated Local Search (ILS) algorithm. The effectiveness of the original Clonal Selection Algorithm for this NP-hard problem is improved by using ILS as a hypermutation operator and VNS as a receptor editing operator. The algorithm is tested on a set of 40 benchmark instances from the literature and ten new best solutions are found. Comparisons of the proposed algorithm with several algorithms from the literature (two versions of the Particle Swarm Optimization algorithm, a Differential Evolution algorithm and a Genetic Algorithm) are also reported.

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References

  1. Bianchi, L., Birattari, M., Manfrin, M., Mastrolilli, M., Paquete, L., Rossi-Doria, O., Schiavinotto, T.: Hybrid metaheuristics for the vehicle routing problem with stochastic demands. J. Math. Model. Algorithms 5(1), 91–110 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  2. Bianchi, L., Dorigo, M., Gambardella, L.M., Gutjahr, W.J.: A survey on metaheuristics for stochastic combinatorial optimization. Nat. Comput. 8(2), 239–287 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  3. Brabazon, A., O’Neill, M.: Biologically Inspired Algorithms for Financial Modeling. Natural Computing Series. Springer, Berlin (2006)

    Google Scholar 

  4. Christiansen, C.H., Lysgaard, J.: A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands. Oper. Res. Lett. 35, 773–781 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  5. Cuevas, E., Osuna-Enciso, V., Wario, F., Zaldvar, D., Pérez-Cisneros, M., : Automatic multiple circle detection based on artificial immune systems. Expert Syst. Appl. 39, 713–722 (2012)

    Google Scholar 

  6. Dabrowski, J.: Clonal selection algorithm for vehicle routing. In: Proceedings of the 2008 1st International Conference on Information Technology, IT 2008 19–21 May 2008, Gdansk, Poland (2008)

    Google Scholar 

  7. Dasgupta, D. (ed.): Artificial Immune Systems and their Application. Springer, Heidelberg (1998)

    Google Scholar 

  8. Dasgupta, D., Niño, L.F.: Immunological Computation: Theory and Applications. CRC Press, Taylor and Francis Group, Boca Raton (2009)

    Google Scholar 

  9. De Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Heidelberg (2002)

    Google Scholar 

  10. De Castro, L.N., Von Zuben, F.J.: The clonal selection algorithm with engineering applications. In: Workshop on Artificial Immune Systems and Their Applications (GECCO00), Las Vegas, NV, pp. 36–37 (2000)

    Google Scholar 

  11. De Castro, L.N., Von Zuben, F.J.: Learning and optimization using the clonal selection principle. IEEE Trans. Evol. Comput. 6(3), 239–251 (2002)

    Article  Google Scholar 

  12. Engelbrecht, A.P.: Computational Intelligence: An Introduction, 2nd edn. Wiley, New York (2007)

    Book  Google Scholar 

  13. Flower, D., Timmis, J. (eds.): In Silico Immunology. Springer, New York (2007)

    Google Scholar 

  14. Forrest, S., Perelson, A. Allen, L., Cherukuri, R.: Self-nonself discrimination in a computer. In: Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy, pp. 202–212. IEEE Computer Society Press, Los Alamitos (1994)

    Google Scholar 

  15. Gong, M., Jiao, L., Zhang, L.: Baldwinian learning in clonal selection algorithm for optimization. Inf. Sci. 180, 1218–1236 (2010)

    Article  Google Scholar 

  16. Goodson, J.C., Ohlmann, J.W., Thomas, B.W.: Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand. Eur. J. Oper. Res. 217, 312–323 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  17. Hansen, P., Mladenovic, N.: Variable neighborhood search: principles and applications. Eur. J. Oper. Res. 130, 449–467 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  18. Li, F., Gao, S., Wang, W., Tang, Z.: An adaptive clonal selection algorithm for edge linking problem. IJCSNS Int. J. Comput. Sci. Netw. Secur. 9(7), 57–65 (2009)

    Google Scholar 

  19. Lourenco, H.R., Martin, O., Stützle, T.: Iterated local search. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics. Operations Research and Management Science, vol. 57, pp. 321–353. Kluwer Academic Publishers, Dordrecht (2002)

    Google Scholar 

  20. Ma, J., Shi, G., Gao, L.: An Improved immune clonal selection algorithm and its applications for VRP. In: Proceedings of the IEEE International Conference on Automation and Logistics Shenyang, China, August 2009 (2009)

    Google Scholar 

  21. Marinakis, Y., Iordanidou, G.R., Marinaki, M.: Particle swarm optimization for the vehicle routing problem with stochastic demands. Appl. Soft Comput. 13, 1693–1704 (2013)

    Article  Google Scholar 

  22. Marinakis, Y., Marinaki, M.: Combinatorial expanding neighborhood topology particle swarm optimization for the vehicle routing problem with stochastic demands. In: GECCO: 2013, Genetic and Evolutionary Computation Conference, Amsterdam, The Netherlands, 6–10 July 2013

    Google Scholar 

  23. Marinakis, Y., Marinaki, M., Spanou, P.: A memetic differential evolution algorithm for vehicle routing problem with stochastic demands. In: Fister, I., Fister, I. Jr. (eds.) Adaptation in Computational Intelligence, Adaptation Learning and Optimization (2014). (accepted)

    Google Scholar 

  24. Martin, O., Otto, S.W., Felten, E.W.: Large-step Markov chains for the traveling salesman problem. Complex Syst. 5(3), 299–326 (1991)

    MATH  MathSciNet  Google Scholar 

  25. Panigrahi, B.K., Yadav, S.R., Agrawal, S., Tiwari, M.K.: A clonal algorithm to solve economic load dispatch. Electr. Power Syst. Res. 77, 1381–1389 (2007)

    Article  Google Scholar 

  26. Stewart, W.R., Golden, B.L.: Stochastic vehicle routing: a comprehensive approach. Eur. J. Oper. Res. 14, 371–385 (1983)

    Article  MATH  Google Scholar 

  27. Talbi, E.-G.: Metaheuristics : From Design to Implementation. Wiley, New York (2009)

    Book  Google Scholar 

  28. Timmis, J., Neal, M.: A resource limited artificial immune system for data analysis. In: Timmis, J., Neal, M. (eds.) Research and Development in Intelligent Systems, vol. 14, pp. 19–32. Springer, London (2000)

    Google Scholar 

  29. Ulutas, B.H., Islier, A.A.: A clonal selection algorithm for dynamic facility layout problems. J. Manuf. Syst. 28, 123–131 (2009)

    Article  Google Scholar 

  30. Ulutas, B.H., Kulturel-Konak, S.: An artificial immune system based algorithm to solve unequal area facility layout problem. Expert Syst. Appl. 39(5), 5384–5395 (2012)

    Article  Google Scholar 

  31. Yang, W.H., Mathur, K., Ballou, R.H.: Stochastic vehicle routing problem with restocking. Transp. Sci. 34, 99–112 (2000)

    Article  MATH  Google Scholar 

  32. Yang, J.-H., Sun, L., Lee, H.P., Qian, Y., Liang, Y.-C.: Clonal selection based memetic algorithm for job shop scheduling problems. J. Bionic Eng. 5, 111–119 (2008)

    Article  Google Scholar 

  33. Zhu, Y., Gao, S., Dai, H., Li, F., Tang, Z.: Improved clonal algorithm and its application to traveling salesman problem. IJCSNS Int. J. Comput. Sci. Netw. Secur. 7(8), 109–113 (2007)

    Google Scholar 

  34. http://www.coin-or.org/SYMPHONY/branchandcut/VRP/data/Vrp-All.tgz

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Author information

Authors and Affiliations

  1. School of Production Engineering and Management, Technical University of Crete, 73100, Chania, Greece

    Yannis Marinakis & Magdalene Marinaki

  2. Department of Civil Engineering, Aristotle University of Thessalonike, 54124, Thessalonike, Greece

    Athanasios Migdalas

  3. Industrial Logistics, Luleå Technical University, 97187, Luleå, Sweden

    Athanasios Migdalas

Authors
  1. Yannis Marinakis
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  2. Magdalene Marinaki
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  3. Athanasios Migdalas
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Corresponding author

Correspondence to Yannis Marinakis .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. AT&T Labs Research, Middletown, New Jersey, USA

    Mauricio G.C. Resende

  3. University of Florida, Gainesville, Florida, USA

    Chrysafis Vogiatzis

  4. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Jose L. Walteros

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© 2014 Springer International Publishing Switzerland

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Marinakis, Y., Marinaki, M., Migdalas, A. (2014). A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands. In: Pardalos, P., Resende, M., Vogiatzis, C., Walteros, J. (eds) Learning and Intelligent Optimization. LION 2014. Lecture Notes in Computer Science(), vol 8426. Springer, Cham. https://doi.org/10.1007/978-3-319-09584-4_24

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  • DOI: https://doi.org/10.1007/978-3-319-09584-4_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09583-7

  • Online ISBN: 978-3-319-09584-4

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