Abstract
Non-exhaustive local search methods are fundamental tools in applied branches of computing such as operations research, and in other applications of optimisation. These problems have proven stubbornly resistant to attempts to find generic meta-heuristic toolkits that are both expressive and computationally efficient for the large problem spaces involved. This paper complements recent work on functional abstractions for local search by examining three fundamental operations on the states that characterise allowable and/or intermediate solutions. We describe how three fundamental operations are related, and how these can be implemented effectively as part of a functional local search library.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Note that this is also the type of recombination, so any recombination method could be used at this point, if it was felt that it was appropriate to do so.
- 2.
An illegal decisions would result in an invalid solution, for example sub-loops in a TSP.
- 3.
- 4.
GLPK may be found at http://www.gnu.org/software/glpk/glpk.html
- 5.
glpk-hs is written by Louis Wasserman and may be found in the Haskell libraries at http://hackage.haskell.org/package/glpk-hs
References
Hoos, H., Stützle, T.: Stochastic Local Search: Foundations & Applications. Morgan Kaufmann Publishers Inc., San Francisco (2005)
Contardo, C., Cordeau, J.-F., Gendron, B.: A grasp + ilp-based metaheuristic for the capacitated location-routing problem. Technical report (2011)
Prins, C., Prodhon, C., Ruiz, A., Soriano, P., Calvo, R.W.: Solving the capacitated location-routing problem by a cooperative lagrangean relaxation-granular tabu search heuristic. Transp. Sci. 41(4), 470–483 (2007)
Masrom, S., Siti, A.Z., Hashimah, P.N., Rahman, A.A.: Towards rapid development of user defined metaheuristics hybridisation. Int. J. Softw. Eng. Appl. 5(2), 1–12 (2011)
Senington, R., Duke, D.: Combinators for meta-heuristic search. J. Funct. Program. (2012, Submitted)
Merz, P., Freisleben, B.: Memetic algorithms for the travelling salesman problem. Complex Syst. 13(4), 297–345 (2001)
Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimisation. IEEE Trans. Evol. Comput. 1(1), 67–82 (1997)
Reinelt, G.: TSPLIB - a traveling salesman problem library. INFORMS J. Comput. 3(4), 376–384 (1991). http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/
Li, J., Kwan, R.S.K.: A fuzzy genetic algorithm for driver scheduling. Eur. J. Oper. Res. 147(2), 334–344 (2003)
Burke, E., Hart, E., Kendall, G., Newall, J., Ross, P., Schulenburg, S.: Hyper-heuristics: an emerging direction in modern search technology. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, pp. 457–474. Kluwer, Dordrecht (2003)
Acknowledgements
The authors would like to thank Tim Sheard for all his advice in the final stages of writing this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Senington, R., Duke, D. (2013). Decomposing Metaheuristic Operations. In: Hinze, R. (eds) Implementation and Application of Functional Languages. IFL 2012. Lecture Notes in Computer Science(), vol 8241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41582-1_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-41582-1_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41581-4
Online ISBN: 978-3-642-41582-1
eBook Packages: Computer ScienceComputer Science (R0)