BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Autor
Løkketangen Arne (Molde University College), Oppen Johan (Molde University College,), Oyola Jorge (Molde University College,), Woodruff David L. (Graduate School of Management)
Tytuł
An Attribute Based Similarity Function for VRP Decision Support
Źródło
Decision Making in Manufacturing and Services, 2012, vol. 6, nr 1/2, s. 65-83, tab., rys., bibliogr. 27 poz.
Słowa kluczowe
Podejmowanie decyzji, Ekonomia matematyczna, Algorytmy, Optymalizacja
Decision making, Mathematical economics, Algorithms, Optimalization
Uwagi
summ.
Abstrakt
When solving problems in the real world using optimization tools, the model solved by the tools is often only an approximation of the underlying, real, problem. In these circumstances, a decision maker (DM) should consider a diverse set of good solutions, not just an optimal solution as produced using the model. On the other hand, the same DM will only be interested in seeing a few of the alternative solutions, and not the plethora of solutions often produced by modern search techniques. There is thus a need to distinguish between good solutions using the attributes of solutions. We develop a distance function of the type proposed in the Psychology literature by Tversky (1977) for the class of VRP problems. We base our difference on the underlying structure of solutions. A DM is often interested in focusing on a set of solutions fulfilling certain conditions that are of specific importance that day, or in general, like avoiding a certain road due to construction that day. This distance measure can also be used to generate solutions containing these specific classes of attributes, as the normal search process might not supply enough of these interesting solutions. We illustrate the use of the functions in a Multiobjective Decision Support System (DSS) setting, where the DM might want to see the presence (or absence) of certain attributes, and show the importance of identifying solutions not on the Pareto front. Our distance measure can use any attributes of the solutions, not just those defined in the optimization model. (original abstract)
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Bountoux, B., Feillet, D. (2005), Ant colony optimization for the traveling purchaser problem. Working paper.
  2. Caprara, A. (1999), Sorting permutations by reversals and eulerian cycle permutations. SIAM Journal on Discrete Mathematics, 12(1),91-110.
  3. Cordeau, J.-F., Laporte, G., Mercier, A. (2001), A unified tabu search heuristic for vehicle routing problems with time windows. Journal of the Operations Research Society, 52, 928-936.
  4. Corne, D., Knowles, J., Oates, M. (2000), The pareto envelope-based selection algorithm for multiobjective optimization. In Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., Merelo, J., and Schwefel, H.-P., editors, Parallel Problem Solving from Nature PPSN VI, volume 1917 of Lecture Notes in Computer Science, pages 839-848. Springer Berlin / Heidelberg.
  5. Dana, E., Woodruff, D. (2009), How to select a small set of diverse solutions to mixed integer programming problems: Good news and bad news. Operations Research Letters, 37:255-260.
  6. Dimmock, N., Maddison, I. (2004), Peer-to-peer collaborative spam detection. Crossroads, 11, 4-4.
  7. Glover, F., Laguna, M. (1997), Tabu Search. Kluwer academic publishers.
  8. Goertzel, B. (1997), From Complexity to Creativity: Explorations in Evolutionary, Autopoietic, and Cognitive Dynamics. Kluwer, Dordrecht.
  9. Hamming, R. (1950), Error-detecting and error-correcting codes. Bell System Technical Journal, 29(2), 147-160.
  10. Hartl, R., Hasle, G., Janssens, G. (2006), Special issue on rich vehicle routing problems. Central European Journal of Operations Research, 14, 103-104.
  11. Jozefowiez, N., Semet, F. (2008), Multi-objective vehicle routing problems. European Journal of Operations Research, 189, 293-309.
  12. Laguna, M., Marti, R. (2003), Scatter Search: Methodology and Implementations in C. Kluwer Academic Publishers.
  13. Løkketangen, A., Woodruff, D. (2005), A distance function to support optimized selection decisions. Decision Support Systems, 39, 345-354.
  14. Medin, D., Goldstone, R., Gentner, D. (1993), Respects for similarity. Psychological Review, 100, 254-278.
  15. Oppen, J., Løkketangen, A. (2006), Arc routing in a node routing environment. Computers and Operations Research, 33(4), 1033-1055.
  16. Oppen, J., Løkketangen, A., Desrosiers, J. (2010), Solving a rich vehicle routing and inventory problem using column generation. Computers and OR, pp. 1308-1317.
  17. Reeves, C. (2003), Genetic algorithms. In Glover, F. and Kochenberger, G., (eds.), Handbook of Metaheuristics, pp. 55-82, Kluwer Academic Publishers.
  18. Ronald, S. (1998), More distance functions for order based encodings. In Proceedings of the IEEE Conference on Evolutionary Computation, pp. 558-563, IEEE Press.
  19. Ryu, T., Eick, C. (1998), A unified similarity measure for attributes with set or bag of values for database clustering. In The 6th International Workshop on Rough Sets, Data Mining and Granular Computing (RSDMGrC'98).
  20. Ryu, T., Eick, C. (2005), A database clustering methodology and tool. Information Sciences, 171, 29-59.
  21. Seveaux, M., S¨orensen, K. (2005), Permutation distance measures for memetic algorithms with population management. In Extended Abstract Book MIC 2005, Metaheuristic International Conference.
  22. Sӧrensen, K. (2006), Route stability in vehicle routing decisions: A practical approach using meta-heuristics. Central European Journal of Operations Research, 14, 193-207.
  23. S¨orensen, K. (2007), Distance measures based on the edit distance for permutation type representations. Journal of Heuristics, 13, 35-47.
  24. S¨orensen, K., Seveaux, M. (2006), MA - PM: Memetic algorithms with population management. Computers and Operations Research, 33, 1214-1225.
  25. Toth, P., Vigo, D., (eds.) (2002), The Vehicle Routing Problem. Society for Industrial and Applied Mathematics, Philadelphia.
  26. Tversky, A. (1977), Features of similarity. Psychological Review, 84, 327-352.
  27. Wagner, R., Fisher, M. (1974), The string-to-string correction problem. Journal of the Association for Computing Machinery, 21, 168-173.
Cytowane przez
Pokaż
ISSN
2300-7087
Język
eng
URI / DOI
http://dx.doi.org/10.7494/dmms.2012.6.2.65
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu