Abstract
Recent years have witnessed great success of ant based hyper heuristics applying to real world applications. Ant based hyper heuristics intend to explore the heuristic space by traversing the fully connected graph induced by low level heuristics (LLHs). However, existing ant based models treat LLH in an equivalent way, which may lead to imbalance between the intensification and the diversification of the search procedure. Following the definition of meta heuristics, we propose an Ant based Hyper heuristic with SpAce Reduction (AHSAR) to adapt the search over the heuristic space. AHSAR reduces the heuristic space by replacing the fully connected graph with a bipartite graph, which is induced by the Cartesian product of two LLH subsets. With the space reduction, AHSAR enforces consecutive execution of intensification and diversification LLHs. We apply AHSAR to the p-median problem, and experimental results demonstrate that our algorithm outperforms meta heuristics from which LLHs are extracted.
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References
Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Ozcan, E., Woodward, J.R.: A Classification of Hyper-heuristics Approaches. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics, International Series in Operations Research & Management Science. Springer, Heidelberg (2009) (in press)
Burke, E.K., McCollum, B., Meisels, A., Petrovic, S., Qu, R.: A Graph-based Hyper-heuristic for Educational Timetabling Problems. European Journal of Operational Research 176(1), 177–192 (2007)
Privosnik, M.: The Scalability of Evolved On Line Bin Packing Heuristics. In: IEEE Congress on Evolutionary Computation, CEC 2007, pp. 2530–2537 (2007)
Burke, E.K., Kendall, G., Silva, D.L., O’Brien, R., Soubeiga, E.: An Ant Algorithm Hyperheuristic for the Project Presentation Scheduling Problem. In: The 2005 IEEE Congress on Evolutionary Computation, vol. 3, pp. 2263–2270 (2005)
Cuesta-Cañada, A., Garrido, L., Terashima-Marín, H.: Building Hyper-heuristics Through Ant Colony Optimization for the 2D Bin Packing Problem. In: Knowledge-Based Intelligent Information and Engineering Systems, pp. 654–660. Springer, Heidelberg (2005)
Chen, P.C., Kendall, G., Berghe, G.: An Ant Based Hyper-heuristic for the Travelling Tournament Problem. In: IEEE Symposium on Computational Intelligence in Scheduling, SCIS 2007, pp. 19–26 (2007)
Holland, J.H.: Adaptation in Natural and Artificial Systems. MIT Press, Cambridge (1992)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B 26(1), 29–41 (1996)
Glover, F.: Tabu search – Part I. ORSA J. on Computing 1, 190–206 (1989)
Glover, F.: Tabu search – Part II. ORSA J. on Computing 2, 4–32 (1990)
Hansen, P., Mladenović, N.: Variable Neighborhood Search: Principles and Applications. European Journal of Operational Research 130(3), 449–467 (2001)
Feo, T.A., Resende, M.G.C.: Greedy Randomized Adaptive Search Procedures. Journal of Global Optimization 6(2), 109–133 (1995)
Taillard, É.D., Gambardella, L.M., Gendreau, M., Potvin, J.Y.: Adaptive Memory Programming: A Unified View of Metaheuristics. European Journal of Operational Research 135(1), 1–16 (2001)
Osman, I.H., Laporte, G.: Metaheuristics: A Bibliography. Annals of Operations Research 63(5), 511–623 (1996)
Taillard, É.D.: Ant Systems. In: Pardalos, P., Resende, M.G.C. (eds.) Handbook of Applied Optimization, pp. 130–137. Oxford Univ. Press, Oxford (2002)
Hansen, P., Mladenović, N.: Variable Neighborhood Search for the p-Median. Location Science 5(4), 207–226 (1997)
Kochetov, Y., Levanova, T., Alekseeva, E., Loresh, M.: Large Neighborhood Local Search for the p-Median Problem. Yugoslav Journal of Operations Research 15(1), 53–63 (2005)
Alp, O., Erkut, E., Drezner, Z.: An Efficient Genetic Algorithm for the p-Median Problem. Annals of Operations Research 122, 21–42 (2003)
Teitz, M.B., Bart, P.: Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph. Operations Research 16(5), 955–961 (1968)
Resende, M.G.C., Werneck, R.F.: A Hybrid Heuristic for the p-Median Problem. Journal of Heuristics 10(1), 59–88 (2004)
Beasley, J.E.: A Note on Solving Large p-Median Problems. European Journal of Operational Research 21, 270–273 (1985)
Reinelt, G.: TSPLIB–A Traveling Salesman Problem Library. ORSA Journal on Computing 3, 376–384 (1991)
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Ren, Z., Jiang, H., Xuan, J., Luo, Z. (2010). Ant Based Hyper Heuristics with Space Reduction: A Case Study of the p-Median Problem. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15844-5_55
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DOI: https://doi.org/10.1007/978-3-642-15844-5_55
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