The Attribute Based Hill Climber

  • Ian M. Whittley
  • George D. Smith
Article

Abstract

In this paper we introduce the Attribute Based Hill Climber, a parameter-free algorithm that provides a concrete, stand-alone implementation of a little used technique from the Tabu Search literature known as “regional aspiration”. Results of applying the algorithm to two classical optimisation problems, the Travelling Salesman Problem and the Quadratic Assignment Problem, show it to be competitive with existing general purpose heuristics in these areas.

local search metaheuristics aspiration travelling salesman problem quadratic assignment problem 

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References

  1. 1.
    Ahuja, R., Orlin, J. B. and Tivari, A.: A greedy genetic algorithm for the quadratic assignment problem, Comput. Oper. Res. 27(10) (2000), 917–934.Google Scholar
  2. 2.
    Anstreicher, K. M., Brixius, N. W., Goux, J.-P. and Linderoth, J.: Solving large quadratic assignment problems on computational grids, Technical Report, Iowa City, IA 52242, 2000.Google Scholar
  3. 3.
    Applegate, D., Bixby, R., Chvatal, C. and Cook, W.: Concorde: Combinatorial optimization and networked combinatorial optimization research and development environment. Available at www.keck.caam.rice.edu/concorde.html.Google Scholar
  4. 4.
    Battiti, R. and Tecchioli, G.: The reactive tabu search, ORSA J. Comput. 6(2) (1994), 126–140.Google Scholar
  5. 5.
    Burkard, R. E., Karisch, S. E. and Rendl, F.: QAPLIB-a quadratic assignment problem library, European J. Oper. Res. 55 (1991), 115–119.Google Scholar
  6. 6.
    Colorni, A. and Maniezzo, V.: The ant system applied to the quadratic assignment problem, Knowledge and Data Engineering 11(5) (1999), 769–778.Google Scholar
  7. 7.
    De Reyck, B. and Herroelen, W.: The multi-mode resource-constrained project scheduling problem with generalized precedence relations, European J. Oper. Res. 119 (1999), 538–556.Google Scholar
  8. 8.
    Dorigo, M. and Gambardella, L. M.: Ant colony systems: A cooperative learning approach to the traveling salesman problem, IEEE Trans. Evolutionary Comput. 1(1) (1997), 53–66.Google Scholar
  9. 9.
    Dorigo, M., Gambardella, L. M. and Taillard, E. D.: Ant colonies for the quadratic assignment problem, J. Oper. Res. Soc. 50 (1999), 167–176.Google Scholar
  10. 10.
    Glover, F. and Laguna, M.: Tabu Search, Kluwer Academic Publishers, Boston, 1997.Google Scholar
  11. 11.
    Knox, J.: Tabu search performance on the symmetric traveling salesman problem, Comput. Oper. Res. 21 (1994), 867–876.Google Scholar
  12. 12.
    Koopmans, T. C. and Beckman, M. J.: Assignment problems and the locations of exonomic activities, Econometrica 25 (1957), 53–76.Google Scholar
  13. 13.
    Larrañaga, P., Kuijpers, C., Murga, R., Inza, I. and Dizdarevic, S.: Genetic algorithms for the travelling salesman problem: A review of representations and operators, Articial Intelligence Review 13 (1999), 129–170.Google Scholar
  14. 14.
    Li, Y., Pardalos, P. M. and Resende, M. G. C.: A greedy randomised adaptive search procedure for the quadratic assignment problem, DIMACS Ser. Discrete Math. Theoret. Comput. Sci. 16 (1994), 237–261.Google Scholar
  15. 15.
    Martin, O. C. and Otto, S. W.: Combining simulated annealing with local search heuristics, Ann. Oper. Res. 63 (1996), 57–75.Google Scholar
  16. 16.
    Mills, P., Tsang, E. and Ford, J.: Applying an extended guided local search to the quadratic assignment problem, Ann. Oper. Res. 118 (2003), 121–135.Google Scholar
  17. 17.
    Nugent, C. E., Vollman, T. E. and Ruml, J.: An experimental comparison of techniques for the assignment of facilities to locations, Oper. Res. 16 (1968), 150–173.Google Scholar
  18. 18.
    Reeves, C. R. (ed.): Modern Heuristic Techniques for Combinatorial Optimization, McGraw-Hill International, New York, 1995.Google Scholar
  19. 19.
    Reinelt, G.: TSPLIB-a traveling salesman problem library, ORSA J. Comput. 3(4) (1991), 376–384.Google Scholar
  20. 20.
    Taillard, E. D.: Robust taboo search for the quadratic assignment problem, Parallel Comput. 17 (1991), 443–455.Google Scholar
  21. 21.
    Van Laarhoven, P. J. M. and Aarts, E. H. L.: Simulated Annealing: Theory and Applications, Kluwer Academic Publishers, Dordrecht, 1998.Google Scholar
  22. 22.
    Voudouris, V.: Guided local search for combinatorial optimisation problems, Ph.D. thesis, Department of Computer Science, University of Essex, 1997.Google Scholar
  23. 23.
    Voudouris, C. and Tsang, E. P. K.: Guided local search and its application to the traveling salesman problem, European J. Oper. Res.113 (1999), 469–499.Google Scholar
  24. 24.
    Whittley, I. M.: Tabu search-revisited, Ph.D. thesis, School of Information Systems, University of East Anglia, 2002.Google Scholar
  25. 25.
    Wilhelm, M. R. and Ward, T. L.: Solving quadratic assignment problems by simulated annealing, IEE Transaction 19 (1987), 107–119.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Ian M. Whittley
    • 1
  • George D. Smith
    • 1
  1. 1.School of Computing SciencesUniversity of East Anglia (UEA)NorwichUK

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