Skip to main content
Log in

Dynamic tabu search strategies for the traveling purchaser problem

  • Tabu Search
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Tabu search is a metastrategy for guiding known heuristics to overcome local optimality with a large number of successful applications reported in the literature. In this paper we investigate two dynamic strategies, the reverse elimination method and the cancellation sequence method. The incorporation of strategic oscillation as well as a combination of these methods are developed. The impact of the different methods is shown with respect to the traveling purchaser problem, a generalization of the classical traveling salesman problem. The traveling purchaser problem is the problem of determining a tour of a purchaser buying several items in different shops by minimizing the total amount of travel and purchase costs. A comparison of the tabu search strategies with a simulated annealing approach is presented, too.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. G. Clarke and J.W. Wright, Scheduling of vehicles from a central depot to a number of delivery points, Operations Research 12(1964)568–581.

    Google Scholar 

  2. F. Dammeyer, P. Forst and S. Voß, On the cancellation sequence method of tabu search, ORSA Journal on Computing 3(1991)262–265.

    Google Scholar 

  3. F. Dammeyer and S. Voß, Application of tabu search strategies for solving multiconstraint zero-one knapsack problems, Working Paper, TH Darmstadt (1991).

  4. F. Dammeyer and S. Voß, Dynamic tabu list management using the reverse elimination method, Annals of Operations Research 41(1993)31–46.

    Article  Google Scholar 

  5. W. Domschke, P. Forst and S. Voß, Tabu search techniques for the quadratic semi-assignment problem, in:New Directions for Operations Research in Manufacturing, ed. G. Fandel, T. Gulledge and A. Jones (Springer, Berlin, 1992) pp. 389–405.

    Google Scholar 

  6. K.A. Dowsland, Simulated annealing, in:Modern Heuristic Techniques for Combinatorial Problems, ed. C.R. Reeves (Blackwell, Oxford, 1993) pp. 20–69.

    Google Scholar 

  7. M.R. Garey and D.S. Johnson,Computers and Intractability: A Guide to the Theory of NP-Completeness (Freeman, San Francisco, 1979).

    Google Scholar 

  8. F. Glover, Tabu search - part I, ORSA Journal on Computing 1(1989)190–206.

    Google Scholar 

  9. F. Glover, Tabu search - part II, ORSA Journal on Computing 2(1990)4–32.

    Google Scholar 

  10. F. Glover and M. Laguna, Tabu search, in:Modern Heuristic Techniques for Combinatorial Problems, ed. C.R. Reeves (Blackwell, Oxford, 1993) pp. 70–150.

    Google Scholar 

  11. F. Glover, M. Laguna, E. Taillard and D. de Werra (eds.),Tabu Search, Annals of Operations Research 41 (Baltzer, Basel, 1993).

    Google Scholar 

  12. B. Golden, L. Levy and R. Dahl, Two generalizations of the traveling salesman problem, Omega 9(1981)439–441.

    Article  Google Scholar 

  13. S.K. Jacobsen, Heuristics for the capacitated plant location model, European Journal of Operational Research 12(1983)253–261.

    Article  Google Scholar 

  14. R.K. Karg and G.L. Thompson, A heuristic approach to solving traveling salesman problems, Management Science 10(1964)225–248.

    Google Scholar 

  15. J.P. Kelly, B.L. Golden and A.A. Assad, Large-scale controlled rounding using tabu search with strategic oscillation, Annals of Operations Research 41(1993)69–84.

    Article  Google Scholar 

  16. S. Lin and B.W. Kernighan, An effective heuristic algorithm for the traveling salesman problem, Operations Research 21(1973)498–516.

    Google Scholar 

  17. N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller and E. Teller, Equation of state calculation by fast computing machines, Journal of Chemical Physics 21(1953)1087–1091.

    Article  Google Scholar 

  18. H.L. Ong, Approximate algorithms for the travelling purchaser problem, Operations Research Letters 1(1982)201–205.

    Article  Google Scholar 

  19. I.H. Osman, Heuristics for the generalised assignment problem: Simulated annealing and tabu search approaches, OR Spektrum 17(1995)211–225.

    Article  Google Scholar 

  20. I.H. Osman and N. Christofides, Capacitated clustering problems by hybrid simulated annealing and tabu search, International Transactions in Operational Research 1(1994)317–336.

    Article  Google Scholar 

  21. H. Paessens and H.K. Weuthen, Tourenplanung in städtischen Straßennetzen mit einem heuristischen Verfahren, in:Tourenplanung bei der Abfallbeseitigung, ed. H.H. Hahn (Schmidt, Bielefeld, 1977) pp. 101–130.

    Google Scholar 

  22. T. Ramesh, Travelling purchaser problem, Opsearch 18(1981)78–91.

    Google Scholar 

  23. S. Voß, ADD- and DROP-procedures for the travelling purchaser problem, Methods of Operations Research 53(1986)317–318.

    Google Scholar 

  24. S. Voß, The traveling purchaser problem with fixed costs, Working Paper, TH Darmstadt (1989).

  25. S. Voß,Steiner-Probleme in Graphen (Hain, Frankfurt am Main, 1990).

    Google Scholar 

  26. S. Voß, Intelligent search, Manuscript, TH Darmstadt (1993).

  27. S. Voß, Solving quadratic assignment problems using the reverse elimination method, in:The Impact of Emerging Technologies on Computer Science and Operations Research, ed. S.G. Nash and A. Sofer (Kluwer, Dordrecht, 1995) pp. 281–296.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Voß, S. Dynamic tabu search strategies for the traveling purchaser problem. Ann Oper Res 63, 253–275 (1996). https://doi.org/10.1007/BF02125457

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02125457

Keywords

Navigation