Abstract
Matheuristics are heuristic algorithms made by the interoperation of metaheuristics and mathematic programming (MP) techniques. An essential feature is the exploitation in some part of the algorithms of features derived from the mathematical model of the problems of interest, thus the definition “model-based metaheuristics” appearing in the title of some events of the conference series dedicated to matheuristics [1]. The topic has attracted the interest of a community of researchers, and this led to the publication of dedicated volumes and journal special issues, [13], [14], besides to dedicated tracks and sessions on wider scope conferences.
The increasing maturity of the area permits to outline some trends and possibilities offered by matheuristic approaches. A word of caution is needed before delving into the subject, because obviously the use of MP for solving optimization problems, albeit in a heuristic way, is much older and much more widespread than matheuristics. However, this is not the case for metaheuristics, and also the very idea of designing MP methods specifically for heuristic solution has innovative traits, when opposed to exact methods which turn into heuristics when enough computational resources are not available.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Matheuristics conferences page (2009), http://astarte.csr.unibo.it/matheuristics
Aggarwal, C., Orlin, J., Tai, R.: An optimized crossover for the maximum independent set. Operations Research 45, 226–234 (1997)
Ahuja, R., Ergun, O., Orlin, J., Punnen, A.: A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics 123(1-3), 75–102 (2002)
Bartolini, E., Mingozzi, A.: Algorithms for the non-bifurcated network design problem. J. of Heuristics 15(3), 259–281 (2009)
Boschetti, M., Jelasity, M., Maniezzo, V.: A fully distributed lagrangean metaheuristic for a p2p overlay network design problem. In: Hartl, R. (ed.) Proceedings MIC 2005 (2005)
Boschetti, M., Maniezzo, V.: Benders decomposition, lagrangean relaxation and metaheuristic design. J. of Heuristics 15(3), 283–312 (2009)
Congram, R., Potts, C., Van de Velde, S.: An iterated dynasearch algorithm for the single-machine total weighted tardiness scheduling problem. INFORMS Journal on Computing 14(1), 52–67 (2002)
Dumitrescu, I., Stützle, T.: Usages of exact algorithms to enhance stochastic local search algorithms. In: Maniezzo, V., Stützle, T., Voss, S. (eds.) Matheuristics: Hybridizing metaheuristics and mathematical programming, OR/CS Interfaces Series. Springer, Heidelberg (2009)
Fischetti, M., Lodi, A.: Local branching. Mathematical Programming B 98, 23–47 (2003)
Gabrielli, R., Guidazzi, A., Boschetti, M.A., Roffilli, M., Maniezzo, V.: Practical origin-destination traffic flow estimation. In: Proc. Third International Workshop on Freight Transportation and Logistics (Odysseus 2006), Altea, Spain (2006)
Maniezzo, V., Boschetti, M., Jelasity, M.: An ant approach to membership overlay design. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 37–48. Springer, Heidelberg (2004)
Maniezzo, V., Boschetti, M., Roffilli, M.: Matheuristics in simulation: a case study in water supply management. In: Caserta, M., Voss, S. (eds.) Proceedings MIC 2009, VIII Metaheuristic International Conference (2009)
Maniezzo, V., Stützle, T., Voss, S. (eds.): Matheuristics: Hybridizing Metaheuristics and Mathematical Programming. Annals of Information Systems, vol. 10. Springer, Heidelberg (2009)
Maniezzo, V., Voss, S., Hansen, P.: Special issue on mathematical contributions to metaheuristics editorial. Journal of Heuristics 15(3) (2009)
Sniedovich, M., Voss, S.: The corridor method: a dynamic programming inspired metaheuristic. Control and Cybernetics 35(3), 551–578 (2006)
Wardrop, J.G.: Some theoretical aspects of road traffic research, volume PART II, vol. 1. Institute of Civil Engineers, Palo Alto (1952)
Yagiura, M., Ibaraki, T.: The use of dynamic programming in genetic algorithms for permutation problems. European Journal of Operational Research 92, 387–401 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Boschetti, M.A., Maniezzo, V., Roffilli, M., Bolufé Röhler, A. (2009). Matheuristics: Optimization, Simulation and Control. In: Blesa, M.J., Blum, C., Di Gaspero, L., Roli, A., Sampels, M., Schaerf, A. (eds) Hybrid Metaheuristics. HM 2009. Lecture Notes in Computer Science, vol 5818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04918-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-04918-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04917-0
Online ISBN: 978-3-642-04918-7
eBook Packages: Computer ScienceComputer Science (R0)