Abstract
In this paper, we propose indicators based on the position method of the descriptive statistic for the Vehicle Routing Problem with Time Windows (VRPTW). The indicators are based on the calculation of the median; they will serve altogether with the technique of discriminant analysis to select appropriately the algorithm that better solves an instance of the VRPTW.
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References
Thangiah, S.R.: Genetic Algorithms, Tabu Search and Simulated Annealing Methods for Vehicle Routing Problems with Time Windows. In: Chambers, L. (ed.) Practical Handbook of Genetic Algorithms: Complex Structures. CRC Press, Boca Raton (1998)
Toth, P., Vigo, D.: The Vehicle Routing Problem. Monographs on Discrete Mathematics and Applications. SIAM, Philadelphia (2001)
Rascon, C., Octacio, A.: Introducción a la estadística descriptiva (in Spanish). Editorial UNAM (1983)
SPSS, Inc. Headquarters, Chicago, Illinois, http://www.spss.com/es/
Pérez, J., Pazos, R.A., Frausto, J., Rodriguez, G., Romero, D., Cruz, L.: A Statical Approach for Algorithm Selection. In: Ribeiro, C.C., Martins, S.L. (eds.) WEA 2004. LNCS, vol. 3059. Springer, Heidelberg (2004)
Huberty, C.J.: Applied Discriminant Analysis. Wiley Interscience, Chichester (1994)
Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Blanton, J., Wainwright, R.L.: Multiple Vehicle Routing with Time and Capacity Constrainst using Genetic Algorithms. In: Proceedings of the Fifth International Conference on Genetic Algorithms (1993)
Pérez, J., Pazos, R.A., Frausto, J., Rodriguez, G., Cruz, L.: Self-Tuning Mechanism for Genetic Algorithms Parameters an Application to Data-Object Allocation in the Web. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds.) ICCSA 2004. LNCS, vol. 3046. Springer, Heidelberg (2004)
Pérez, J., Pazos, R.A., Fraire, H., Cruz, L., Pecero, J.: Adaptive Allocation of Data-Objects in the Web using Neural Networks. LNCS, vol. 2829. Springer, Heidelberg (2003)
Pérez, J., Pazos, R.A., Fraire, H., Cruz, L., Santiago, E., García, N.E.: A Machine Learning Approach for Modeling Algorithm Performance Predictors. In: Torra, V., Narukawa, Y. (eds.) MDAI 2004. LNCS (LNAI), vol. 3131. Springer, Heidelberg (2004)
Fink, E.: How to Solve it Automatically, Selection among Problem-solving Methods. In: Proceedings of the Fourth International Conference on AI Planning Systems AIPS 1998, pp. 128–136 (1998)
Pérez, J., Pazos, R.A., Frausto, J., Rodriguez, G., Cruz, L.: Comparison and Selection of Exact and Heuristic Algorithm. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds.) ICCSA 2004. LNCS, vol. 3045. Springer, Heidelberg (2004)
Borghetti, B.J.: Inference algorithm Performance and Selection under Constrained Resources. MS Thesis. AFIT/GCS/ENG/96D-05 (1996)
Soares, C., Brazdil, P.: Zoomed Ranking, Selection of Classification Algorithms Based on Relevant Performance Information. In: Zighed, A.D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 126–135. Springer, Heidelberg (2000)
Michie, D., Spiegelhalter, D.J., Taylor, C.C.: Machine Learning, Neural and Statistical Classification. Ellis Horwood (1994) ISBN: 978-0131063600
Wagner, S., Affenzeller, M.: HeuristicLab: A Generic and Extensible Optimization Environment. Adaptive and Natural Computing Algorithms. Springer Computer Science, pp. 538–541 (2005)
Affenzeller, M.: New Generic Hybrids Based Upon Genetic Algorithms. Advances in Artificial Intelligence. In: Garijo, F.J., Riquelme, J.-C., Toro, M. (eds.) IBERAMIA 2002. LNCS (LNAI), vol. 2527, pp. 329–339. Springer, Heidelberg (2002)
Solomon, M.M.: Algorithms for Vehicle Routing and Scheduling Problems with Time Window Constrains. Operations Research 35 (1987)
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Ruiz-Vanoye, J.A., Zárate M., J.A., Díaz-Parra, O., Landero N., V. (2008). Applied Statistical Indicators to the Vehicle Routing Problem with Time Windows for Discriminate Appropriately the Best Algorithm. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69848-7_90
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DOI: https://doi.org/10.1007/978-3-540-69848-7_90
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