Abstract
A metaheuristic for solving complex problems is proposed. The introduced Sensitive Robot Metaheuristic (SRM) is based on the Ant Colony System optimization technique. The new model relies on the reaction of virtual sensitive robots to different stigmergic variables. Each robot is endowed with a particular stigmergic sensitivity level ensuring a good balance between search diversification and intensification. Comparative tests are performed on large-scale NP-hard robotic travel problems. These tests illustrate the effectiveness and robustness of the proposed metaheuristic.
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References
Bixby, B., Reinelt, G.: (1995), http://nhse.cs.rice.edu/softlib/catalog/tsplib.html
Bonabeau, E., Dorigo, M., Tehraulaz, G.: Swarm intelligence from natural to artificial systems. Oxford University Press, Oxford, UK (1999)
Dorigo, M., Gambardella, L.M.: Ant Colony System: A cooperative learning approach to the Traveling Salesman Problem. IEEE Trans. Evol. Comp. 1, 53–66 (1997)
Fischetti, M., Gonzales, J.J.S., Toth, P.: A Branch-and-Cut Algorithm for the Symmetric Generalized Travelling Salesman Problem. Oper. Res. 45(3), 378–394 (1997)
Golden, B.L., Assad, A.A.: A decision-theoretic framework for comparing heuristics. European J. of Oper. Res. 18, 167–171 (1984)
Grassé, P.-P.: La Reconstruction du Nid et Les Coordinations Interindividuelles Chez Bellicositermes Natalensis et Cubitermes sp. La Thorie de la Stigmergie: Essai dinterpretation du Comportement des Termites Constructeurs. Insect Soc. 6, 41–80 (1959)
Helsgaun, K.: An effective implementation of the lin-kernighan TSP heuristic. European Journal of Operations Research 126, 106–130 (2000)
Johnson, D.S., McGeoch, L.A.: Local Search in Combinatorial Optimization, chapter The Traveling Salesman Problem: A Case Study in Local Optimization, pp. 215–310. John Wiley & Sons, New York (1997)
Johnson, D.S., McGeoch, L.A.: The Traveling Salesman Problem and its Variations, chapter Experimental Analysis of Heuristics for the STSP, pp. 369–443. Kluwer Academic Publishers, Dordrecht (2002)
Pintea, C-M., Pop, C.P., Chira, C.: The Generalized Traveling Salesman Problem solved with Ant Algorithms. J.UCS (in press, 2007)
Renaud, J., Boctor, F.F.: An efficient composite heuristic for the Symmetric Generalized Traveling Salesman Problem. Euro. J. Oper. Res. 108(3), 571–584 (1998)
Snyder, L.V., Daskin, M.S.: A Random-Key Genetic Algorithm for the Generalized Traveling Salesman Problem. INFORMS, San Antonio, TX (2000)
Theraulaz, G., Bonabeau, E.: A brief history of stigmergy. Artificial Life 5(2), 97–116 (1999)
White, T.: Expert Assessment of Stigmergy: A Report for the Department of National Defence, http://www.scs.carleton.ca/arpwhite/stigmergy-report.pdf
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Pintea, CM., Chira, C., Dumitrescu, D., Pop, P.C. (2008). A Sensitive Metaheuristic for Solving a Large Optimization Problem. In: Geffert, V., Karhumäki, J., Bertoni, A., Preneel, B., Návrat, P., Bieliková, M. (eds) SOFSEM 2008: Theory and Practice of Computer Science. SOFSEM 2008. Lecture Notes in Computer Science, vol 4910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77566-9_48
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DOI: https://doi.org/10.1007/978-3-540-77566-9_48
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