Advertisement

Annals of Operations Research

, Volume 41, Issue 1, pp 1–28 | Cite as

A user's guide to tabu search

  • Fred Glover
  • Eric Taillard
  • Eric Taillard
Tabu Search: An Introduction

Abstract

We describe the main features of tabu search, emphasizing a perspective for guiding a user to understand basic implementation principles for solving combinatorial or nonlinear problems. We also identify recent developments and extensions that have contributed to increasing the efficiency of the method. One of the useful aspects of tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model elements, such as new types of constraints and objective functions. Similarly, the method itself can be evolved to varying levels of sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns of tabu search, and to show how they may be exploited in various contexts. Our presentation is motivated by the emergence of an extensive literature of computational results, which demonstrates that a well-tuned implementation makes it possible to obtain solutions of high quality for difficult problems, yielding outcomes in some settings that have not been matched by other known techniques.

Keywords

Tabu search heuristics combinatorial optimization artificial intelligence 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    R.E. Burkard, Quadratic assignment problems, Eur. J. Oper. Res. 15(1984)283–289.Google Scholar
  2. [2]
    J. Chakrapani and J. Skorin-Kapov, Massively parallel tabu search for quadratic assignment problem, Ann. Oper. Res. (1993), this volume.Google Scholar
  3. [3]
    Committee on the Next Decade of Operations Research (Condor), Operations research: The next decade, Oper. Res. 36(1988).Google Scholar
  4. [4]
    D. Costa, A tabu search algorithm for computing an operational time table, Working Paper, Département de Mathématiques, École Polytechnique Fédérale de Lausanne, Switzerland (1990).Google Scholar
  5. [5]
    F. Dammeyer and S. Voss, Dynamic tabu list management using the reverse elimination method, Ann. Oper Res. (1993), this volume.Google Scholar
  6. [6]
    C.N. Fiechter, A parallel tabu search algorithm for large scale traveling salesman problems, Working Paper 90/1, Département de Mathématiques, Ècole Polythechnique Fédérale de Lausanne, Switzerland (1990).Google Scholar
  7. [7]
    G. Finke, R.E. Burkard and F. Rendl, Quadratic assignment problems, Ann. Discr. Math. 31(1987)61–82.Google Scholar
  8. [8]
    A. Frieze, J. Yadegas, S. El-Horbaty and D. Parkinson, Algorithms for assignment problems on an array processor, Parallel Comp. 11(1989)151–162.Google Scholar
  9. [9]
    B. Gavish, Manifold search techniques applied to the quadratic assignment problem, Technical Report, Owen Graduate School of Management, Vanderbilt University (1991).Google Scholar
  10. [10]
    M. Gendreau, A. Hertz and G. Laporte, New intersection and post-optimization procedures for the traveling salesman problem, CRT-708, Centre de Recherche sur les Transports, Université de Montréal (1990).Google Scholar
  11. [11]
    M. Gendreau, A. Hertz and G. Laporte, A tabu search heuristics for the vehicle routing problem, CRT-777, Centre de Recherche sur les Transports, Université de Montréal (1991) to appear in Manag. Sci.Google Scholar
  12. [12]
    F. Glover, Heuristics for integer programming using surrogate constraints, Dec. Sci. 8(1977)156–166.Google Scholar
  13. [13]
    F. Glover, Future paths for integer programming and links to artificial intelligence, Comp. Oper. Res. 13(1986)533–549.Google Scholar
  14. [14]
    F. Glover, Tabu search-Part I, ORSA J. Comput. 1(1989)190–206.Google Scholar
  15. [15]
    F. Glover, Candidate list strategies and tabu search, CAAI Research Report, University of Colorado, Boulder (July 1989).Google Scholar
  16. [16]
    F. Glover, Tabu search-Part II, ORSA J. Comput. 2(1990)4–32.Google Scholar
  17. [17]
    F. Glover, Tabu search for nonlinear and parametric optimization (with links to genetic algorithms), Technical Report, Graduate School of Business and Administration, University of Colorado at Boulder (1991), to appear in Discr. Appl. Math.Google Scholar
  18. [18]
    F. Glover, R. Glover and D. Klingman, The threshold assignment algorithm, Math. Progr. Study 26(1986)12–37.Google Scholar
  19. [19]
    F. Glover, D. Klingman and N. Phillips, A network related nuclear power plant model with an intelligent branch and bound solution approach, Ann. Oper. Res. 21(1990)317–332.Google Scholar
  20. [20]
    P. Hansen, The steepest ascent mildest descent heuristic for combinatorial programming,Congress on Numerical Methods in Combinatorial Optimization, Capri, Italy (1986).Google Scholar
  21. [21]
    P. Hansen and B. Jaumard, Algorithms for the maximum satisfiability problem, Computing 44(1990)279–303.Google Scholar
  22. [22]
    A. Hertz and D. de Werra, Using tabu search technique for graph coloring, Computing 39(1987)345–451.Google Scholar
  23. [23]
    A. Hertz and D. de Werra, Informatique et Horaires Scolaires, Output 12(1989)53–56.Google Scholar
  24. [24]
    D. Johnson, Local optimization and the traveling salesman problem,Proc. 17th Annual Colloquim on Automata, Languages and Programming (Springer, 1990) pp. 446–461.Google Scholar
  25. [25]
    J.P. Kelly, B.L. Golden and A.A. Assad, Large-scale controlled rounding using tabu search with strategic oscillation, Ann. Oper. Res. (1993), this volume.Google Scholar
  26. [26]
    J. Knox, The application of tabu search to the symmetric traveling salesman problem, Ph.D. thesis, Graduate School of Business, University of Colorado.Google Scholar
  27. [27]
    A. Kohlen and D. Pesch, Genetic local search in combinatorial optimization, to appear in Discr. Appl. Math. (1991).Google Scholar
  28. [28]
    M. Laguna, J.W. Barnes and F. Glover, Tabu search methods for a single machine scheduling problem, J. Int. Manufacturing 2(1991)63–74.Google Scholar
  29. [29]
    M. Laguna and F. Glover, Integrating target analysis and tabu search for improved scheduling systems, School of Business, University of Colorado, Boulder (1991), to appear in Expert Systems with Application: An International Journal.Google Scholar
  30. [30]
    S. Lin and B.W. Kernighan, An effective heuristic algorithm for the traveling salesman problem, Oper. Res. 21(1973)498–516.Google Scholar
  31. [31]
    M. Malek, M. Guruswamy, H. Owens and M. Pandya, Serial and parallel search techniques for the traveling salesman problem, Ann. Oper. Res. (1989).Google Scholar
  32. [32]
    E.L. Mooney and R.L. Rardin, Tabu search for a class of scheduling problems, Ann. Oper. Res. (1993), this volume.Google Scholar
  33. [33]
    H. Muhlenbein, Parallel genetic algorithms and combinatorial optimization, to appear in SIAM J. Optim. (1991).Google Scholar
  34. [34]
    I.H. Osman, Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem, Ann. Oper. Res. (1993), this volume.Google Scholar
  35. [35]
    P.S. Ow and T.E. Morton, Filtered beam search in scheduling, Int. J. Prod. Res. 26(1988)35–62.Google Scholar
  36. [36]
    E. Rolland and H. Pirkul, Heuristic search for graph partitioning,31st Joint National TIMS/ORSA Meeting, Nashville, TN (1991).Google Scholar
  37. [37]
    F. Semet and I. Loewenton, The traveling salesman problem under accessibility constraints, Report ORWP 92/02, DMA, EPFL (1992).Google Scholar
  38. [38]
    F. Semet and E. Taillard, Solving real-life VRPS efficiently using TS, Ann. Oper. Res. (1993), this volume.Google Scholar
  39. [39]
    J. Skorin-Kapov, Extensions of a tabu search adaptation to the quadratic assignment problem, Harriman School Working Paper HAR-90-006, State University of New York at Stony Brook (1990).Google Scholar
  40. [40]
    E. Taillard, Parallel tabu search for the jobshop scheduling problem, Research Report ORWP 89/11, EPFL, DMA Lausanne, Switzerland (1989).Google Scholar
  41. [41]
    E. Taillard, Some efficient heuristic methods for the flowshop sequencing problem, Euro. J. Oper. Res. 47(1990)65–79.Google Scholar
  42. [42]
    E. Taillard, Robust taboo search for the quadratic assignment problem, Parallel Comp. 17(1991)443–455.Google Scholar
  43. [43]
    N. Ulder, E, Aarts, H.-J. Bandelt, P. van Laarhoven and E. Pesch, Genetic local search algorithms for the traveling salesman problem,Proc. 1st Int. Workshop on Parallel Problem Solving, ed. Schwefel and Manner, Lecture Notes in Computer Science 496(1991) pp. 109–116.Google Scholar
  44. [44]
    D. de Werra and A. Hertz, Tabu search tehcniques: A tutorial and an application to neural networks, OR Spectrum (1989)131–141.Google Scholar
  45. [45]
    D. Whitley, T. Starkweather and D. Fuguay, Scheduling problems and traveling salesman: The genetic edge recombinition operator,Proc. 3rd Int. Conf. of Genetic Algorithms, Fairfax, VA (1989).Google Scholar
  46. [46]
    D.L. Woodruff and E. Zemel, Hashing vectors for tabu search, Ann. Oper. Res. (1993), this volume.Google Scholar

Copyright information

© J.C. Baltzer AG, Science Publishers 1993

Authors and Affiliations

  • Fred Glover
    • 1
  • Eric Taillard
    • 2
  • Eric Taillard
    • 2
  1. 1.Graduate School of BusinessUniversity of ColoradoBoulderUSA
  2. 2.Department of MathematicsSwiss Federal Institute of TechnologyLausanneSwitzerland

Personalised recommendations