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Tabu Search and Adaptive Memory Programming — Advances, Applications and Challenges

  • Fred Glover
Chapter
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 7)

Abstract

Tabu search (TS) has provided advances for solving difficult optimization problems in many domains. At the same time, fundamental TS strategies are often not applied as effectively as they might be, and their underlying rationale is often not completely understood. We examine basic concepts and principles of tabu search, emphasizing those that have sometimes led to applying the label “adaptive memory programming” to this class of methods.

The goal of this paper is to focus on key themes that are given inadequate attention in many treatments of tabu search. We also examine basic TS strategies that provide useful alternatives to procedures often associated with “evolutionary” or “genetic” algorithms. Specific tabu search applications are also summarized to provide a clearer understanding of settings where the method is being used. Finally, we include an Appendix that identifies the elements of tabu search that are most neglected in implementations, and that can significantly improve its performance.

Keywords

Tabu Search Vehicle Route Problem Facility Layout Quadratic Assignment Problem Vehicle Rout Problem With Time Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Aarts, E.H.L. and J.H.M. Korst (1989). “Boltzmann Machines for Travelling Salesman Problems,” European Journal of Operational Research, 39, 79–95.CrossRefGoogle Scholar
  2. [2]
    Ackley, D. (1987). A Connectionist Model for Genetic Hillclimbing, Kluwer, Dordrecht. Academic Publishers.Google Scholar
  3. [3]
    Aggarwal, C.C., J.B. Orlin, and R.P. Tai (1996). “Optimized Crossover for the Independent Set Problem,” MIT Technical Report, to appear in Operations Research.Google Scholar
  4. [4]
    Aiex, R.M., S.L. Martins, C.C. Ribeiro and N.R. Rodriguez (1996). “Asynchronous parallel strategies for tabu search applied to the partitioning of VLSI circuits,” Research report, Department of Computer Science, Catholic University of Rio de Janeiro.Google Scholar
  5. [5]
    Al-Mahmeed, A.S. (1996). “Tabu Search Combination and Integration,” In Meta- Heurisitcs: Theory and Applications. pp. 319–330, I. H. Osman & J.P. Kelly (eds.), Kluwer Academic Publishers.Google Scholar
  6. [6]
    Andreatta, A.A. and C.C. Ribeiro (1994). “A Graph Partitioning Heuristic for the Parallel Pseudo-exhaustive Logical Test of VLSI Combinational Circuits,” Annals of Operations Research 50, 1–36.CrossRefGoogle Scholar
  7. [7]
    Back, T., F. Hoffmeister and H. Schwefel (1991). “A Survey of Evolution Strategies,” In Proceedings of the Fourth International Conference on Genetic Algorithms, eds. R. Belew and L. Booker, pp. 2–9. Morgan Kaufmann, San Mateo, CA.Google Scholar
  8. [8]
    Balas, E., and W. Niehaus (1996). “Optimized Crossover-Based Genetic Algorithms for the Maximum Cardinality and Maximum Weight Clique Problems,” Management Science Research Report #MSRR-613, submitted to Journal of Heuristics.Google Scholar
  9. [9]
    Barnes, J. Wesley (1993). “Solving the Multiple-Machine Weighted Flow Time Problem Using Tabu Search,” IIE Transactions, Vol 25, Number 2.Google Scholar
  10. [10]
    Barnes, J.W. and W.B. Carlton (1995). “Solving the Vehicle Routing Problem with Time Windows Using Reactive Tabu Search,” presented at the Fall INFORMS Conference in New Orleans, Louisiana, Tuesday, October 31, 1995, in review by the IIE Transactions.Google Scholar
  11. [11]
    Battiti, R., P. Lee, A. Sartori, and G. Tecchiolli (1994a). “Totem: A Digital Processor for Neural Networks and Reactive Tabu Search,” In Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, MICRONEURO 94, pages 17–25.Google Scholar
  12. [12]
    Battiti, R. P. Lee, A. Sartori, and G. Tecchiolli (1994b). “Combinatorial Optimization for Neural Nets: RTS Algorithm and Silicon,” Technical Report no. 9406 - 04, IRST, Trento, IT.Google Scholar
  13. [13]
    Battiti, R. and G.Tecchiolli (1992). “Parallel Based Search for Combinatorial Optimization: Genetic Algorithms and Tabu Search,” Microprocessor and Microsystems, 16: 351–367.CrossRefGoogle Scholar
  14. [14]
    Battiti, R. and G. Tecchiolli (1994b). “The Reactive Tabu Search,” ORSA Journal on Computing, 6 (2): 126–140.CrossRefGoogle Scholar
  15. [15]
    Battiti, R. and G. Tecchiolli (1994c). “Simulated Annealing and Tabu Search in the Long Run: A Comparison on QAP Tasks,” Computer and Mathematics with Applications, 28 (6): 1–8.CrossRefGoogle Scholar
  16. [15]
    Battiti, R. and G. Tecchiolli (1994c). “Simulated Annealing and Tabu Search in the Long Run: A Comparison on QAP Tasks,” Computer and Mathematics with Applications, 28 (6): 1–8.CrossRefGoogle Scholar
  17. [17]
    Battiti, R. and G. Tecchiolli (1995b). “Training Neural Nets with the Reactive Tabu Search,” IEEE Transactions on Neural Networks, 6 (5): 1185–1200CrossRefGoogle Scholar
  18. [18]
    Battiti, R. and G. Tecchiolli (1995c). “Local Search with Memory: Benchmarking RTS,” Operations Research Spektrum, 17 (2/3): 67–86.CrossRefGoogle Scholar
  19. [19]
    Beltran, H.F. and D. Skorin-Kapov (1994). “On Minimum Cost Isolated Failure Immune Networks,” Telecommunication Systems, 3, 183–200.CrossRefGoogle Scholar
  20. [20]
    Błäzewicz, J., P. Hawryluk and R. Walkowiak (1993). “Using a Tabu Search Approach for Solving the Two-dimensional Irregular Cutting Problem,” Annals of Operations Research, 41, 313–325.CrossRefGoogle Scholar
  21. [21]
    Błäzewicz, J. and R. Walkowiak (1995). “A Local Search Approach for Two-dimensional Irregular Cutting,” OR Spectrum, 17, 93–98.CrossRefGoogle Scholar
  22. [22]
    Brumelle, S., D. Granot, M. Halme, and I. Vertinsky (1996). “A Tabu Search Algorithm for Finding a Good Forest Harvest Schedule Satisfying Green-up Constraints,” Forest Economics and Policy Analysis Research Unit The University of British Columbia Vancouver, B.C., CanadaGoogle Scholar
  23. [23]
    Carlton, William B. and J. Wesley Barnes (1995). “A Note on Hashing Functions and Tabu Search Algorithms,” To appear in the European Journal of Operational Research.Google Scholar
  24. [24]
    Carlton, William B. and J. Wesley Barnes (1996). “Solving the Traveling Salesman Problem with Time Windows Using Tabu Search,” to appear in IIE Transactions.Google Scholar
  25. [25]
    Chakrapani, J. and J. Skorin-Kapov (1992). “Connectionist Approaches to the Quadratic Assignment Problem,” Computers and Operations Research, 19 (3/4), 287–295.CrossRefGoogle Scholar
  26. [26]
    Chakrapani, J. and J. Skorin-Kapov (1993). “Connection Machine Implementation of a Tabu Search Algorithm for the Traveling Salesman Problem,” Journal of Computing and Information Technology, 1 (1), 29–36.Google Scholar
  27. [27]
    Chakrapani, J. and J. Skorin-Kapov (1993a). “Massively Parallel Tabu Search for the Quadratic Assignment Problem,” Annals of Operations Research, 41, 327–341.CrossRefGoogle Scholar
  28. [28]
    Chakrapani, J. and J. Skorin-Kapov (1995). Mapping Tasks to Processors to Minimize Communication Time in a Multiprocessor System, The Impact of Emerging Technologies of Computer Science and Operations Research, Kluwer Academic Publishers, 45–64.Google Scholar
  29. [29]
    Chiang, W.-C. and P. Kouvelis (1994a). “Simulated Annealing and Tabu Search Approaches for Unidirectional Flowpath Design for Automated Guided Vehicle Systems,” Annals of Operation Research, Vol. 50.Google Scholar
  30. [30]
    Chiang, W.-C. and P. Kouvelis (1994b). “An Improved Tabu Search Heuristic for Solving Facility Layout Design Problems,” International Journal of Production Research (forthcoming).Google Scholar
  31. [31]
    Chiang, W.-C. and R. Russell (1995). “A Reactive Tabu Search Metahuris-tic for the Vehicle Routing Problem with Time Windows,” submitted to ORSA Journal on Computing, Working Paper, Department of Quantitative Methods and Management Information Systems.Google Scholar
  32. [32]
    Costamagna, F., A. Fanni and G. Giacinto (1995). “Tabu Search for the Optimization of B-ISDN Telecommunication Networks,” Tech. Report, Dept. of Electrical Eng., University of Cagliari, no. 60.Google Scholar
  33. [33]
    Crainic, T.G., M. Toulouse and M. Gendreau (1993a). “A Study of Synchronous Parallelization Strategies for Tabu Search,” Publication 934, Centre de recherche sur les transports, Universite de Montreal, 1993.Google Scholar
  34. [34]
    Crainic, T.G., M. Toulouse, and M. Gendreau (1993b). “Appraisal of Asynchronous Parallelization Approaches for Tabu Search Algorithms,” Publication 935, Center de recherche sur les transports, Universite de Montreal, 1993.Google Scholar
  35. [35]
    Crowston, W.B., F. Glover, G.L. Thompson and J.D. Trawick (1963). “Probabilistic and Parametrick Learning Combinations of Local Job Shop Scheduling Rules,” ONR Research Memorandum No. 117, GSIA, Carnegie-Mellon University, Pittsburg, PA.Google Scholar
  36. [36]
    Daduna, J.R., and S. Voss (1995). “Practical Experiences in Schedule Synchronization,” Lecture Notes in Economics and Mathematical Systems, 430, 39–55.CrossRefGoogle Scholar
  37. [37]
    Dammeyer, F., and S. Voss (1993). “Dynamic Tabu List Management Using the Reverse Elimination Method,” Annals of Operations Research, 41, 31–46.CrossRefGoogle Scholar
  38. [38]
    Davis, L. (1989). “Adapting Operator Probabilities in Genetic Algorithms,” In Proceedings of the Third International Conference on Genetic Algorithms, pp. 61- 69, Morgan Kaufmann, San Mateo, CA.Google Scholar
  39. [39]
    Dell’Amico, M. and M. Trubian (1993). “Applying Tabu Search to the Job-Shop Scheduling Problem,” Annals of Operations Research, Vol. 41, 231–252.CrossRefGoogle Scholar
  40. [40]
    Dell’Amico, M. and Francesco Maffioli (1996). “A New Tabu Search Approach to the 0–1 Equicut Problem,” In Meta-Heuristics: Theory & Applications, pp. 361–378, I. H. Osman & J.P. Kelly (eds.), Kluwer Academic Publishers.Google Scholar
  41. [41]
    Dodin, B., A.A. Elimam and E. Rolland (1996). “Tabu Search in Audit Scheduling,” submitted to the special issue of European Journal of Operation Research on Tabu Search.Google Scholar
  42. [42]
    Domschke, D., P. Forst and S. Voss (1992). “Tabu Search Techniques for the Quadratic Semi-assignment Problem,” In: G. Fandel, T. Gulledge and A. Jones (eds.), New Directions for Operations Research in Manufacturing, Springer, Berlin, 389 - 405.Google Scholar
  43. [43]
    Dorndorf, U. and E. Pesch (1994). “Fast Clustering Algorithms,” ORSA Journal on Computing, 6, 141–153.CrossRefGoogle Scholar
  44. [44]
    Eiben, A.E., P.-E. Raue and Zs. Ruttkay (1994). “Genetic Algorithms with Multi-Parent Recombination,” In Y. Davidor, H.-P Schwefel, and R. Manner (Eds.) Proceedings of the Third International Conference on Parallel Problem Solving from Nature (PPSN) (pp. 78–87 ). New York: Springer-Verlag.Google Scholar
  45. [45]
    Eschelman, L.J. and J.D. Schaffer (1992). “Real-Coded Genetic Algorithms and Interval-Schemata,” Technical Report, Phillips Laboratories.Google Scholar
  46. [46]
    Fanni, A., G. Giacinto and M. Marchesi (1996). “Tabu Search for Continuous Optimization of Electromagnetic Structures,” submitted to Int. Workshop on Optimization and Inverse Problems in Electromagnetism, Brno, Czech Republic, June.Google Scholar
  47. [47]
    Fleurent, C., F. Glover, P. Michelon and Z. Valli (1996). “A Scatter Search Approach for Unconstrained Continuous Optimization,” Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, pp. 643–648.Google Scholar
  48. [48]
    Fréville, A. and G. Plateau (1986). “Heuristics and Reduction Methods for Multiple Constraint 0-1 Linear Programming Problems,” European Journal of Operational Research, 24, 206–215.CrossRefGoogle Scholar
  49. [49]
    Fréville, A. and G. Plateau (1993). “An Exact Search for the Solution of the Surrogate Dual of the 0-1 Bidimensional Knapsack Problem,” European Journal of Operational Research, 68, 413–421.CrossRefGoogle Scholar
  50. [50]
    Glover, F. (1965). “A Multiphase-dual Algorithm for the Zero-one Integer Programming Problem,” Operations Research, 13, 879–919.CrossRefGoogle Scholar
  51. [51]
    Glover, F. (1968). “Surrogate Constraints,” Operations Research, 16, 741–749.CrossRefGoogle Scholar
  52. [52]
    Glover, F. (1975). “Surrogate Constraint Duality in Mathematical Programming,” Operations Research, 23, 434–451.CrossRefGoogle Scholar
  53. [53]
    Glover, F. (1977). “Heuristics for Integer Programming Using Surrogate Constraints,” Decision Sciences, 8, 156–166.CrossRefGoogle Scholar
  54. [54]
    Glover, F. (1989). “Tabu Search, Part I,” ORSA Journal on Computing, 1, 190–206.CrossRefGoogle Scholar
  55. [55] Glover, F. (1992).
    Ejection Chains, Reference Structures and Alternating Path Methods for Traveling Salesman Problems,” University of Colorado. Shortened version published in Discrete Applied Mathematics, 1996, 65, 223–253.CrossRefGoogle Scholar
  56. [56]
    Glover, F. (1994a). “Tabu Search for Nonlinear and Parametric Optimization (with Links to Genetic Algorithms),” Discrete Applied Mathematics, 49, 231–255.CrossRefGoogle Scholar
  57. [57]
    Glover, F. (1994b). “Genetic Algorithms and Scatter Search: Unsuspected Potentials,” Statistics and Computing, 4, 131–140.CrossRefGoogle Scholar
  58. [58]
    Glover, F. (1995a). “Scatter Search and Star-Paths: Beyond the Genetic Metaphor,” OR Spektrum, 17: 125–137.CrossRefGoogle Scholar
  59. [59]
    Glover, F. (1995b). “Tabu Search Fundamentals and Uses.” Graduate School of Business, University of Colorado, condensed version published in Mathematical Programming: State of the Art, 1994, Birge & Murty, eds., 64–92.Google Scholar
  60. [60]
    Glover, F. (1995c) “Tabu Thresholding: Improved Search by Nonmonotonic Trajectories,” ORSA Journal on Computing, Vol. 7, No. 4, 426–442.CrossRefGoogle Scholar
  61. [61]
    Glover, F. and G. Kochenberger (1996). “Critical Event Tabu Search for Multidimensional Knapsack Problems,” In Meta-Heuristics: Theory & Applications, I.H. Osman and J.P. Kelly (eds.), 407–427, Kluwer Academic Publishers, Norwell, MA.Google Scholar
  62. [62]
    Glover, F. and M. Laguna (1993). “Tabu Search,” In Modern Heuristic Techniques for Combinatorial Problems. ed. C. Reeves, pp. 70–141. Blackwell Scientific Publishing, Oxford.Google Scholar
  63. [63]
    Glover, F. and C. McMillan (1986). “The General Employee Scheduling Problem: An Integration of Management Science and Artificial Intelligence,” Computers and Operations Research, 15: 5, 563–593.CrossRefGoogle Scholar
  64. [64]
    Greenberg, H.J. and W.P. Pierskalla (1970). “Surrogate Mathematical Programs,” Operations Research, 18, 924–939.CrossRefGoogle Scholar
  65. [65]
    Greenberg, H.J. and W.P. Pierskalla (1973). “Quasi-conjugate Functions and Surrogate Duality,” Cahiers du Centre d’Etudes de Recherche Operationelle, 15, 437–448.Google Scholar
  66. [66]
    Hansen, P., B. Jaumard and Da Silva (1992). “Average Linkage Divisive Hierarchical Clustering,” to appear in Journal of Classification.Google Scholar
  67. [67]
    Hansen, P., B. Jaumard and M. Poggi di Aragao (1992). “Mixed Integer Column Generation Algorithms and the Probabilistic Maximum Satisfiability Problem,” Proceedings of the 2nd Integer Programming and Combinatorial Optimization Conference, Carnegie Mellon.Google Scholar
  68. [68]
    Hertz, A., B. Jaumard, and M. Poggi di Aragao (1991). “Topology of Local Optima for the K-Coloring Problem,” to appear in Discrete Applied Mathematics.Google Scholar
  69. [69]
    Jaumard, B., P. Hansen, and M. Poggi di Aragao (1991). “Column Generation Methods of Probabilistic Logic,” ORSA Journal on Computing, 3, 135–148.CrossRefGoogle Scholar
  70. [70]
    Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI.Google Scholar
  71. [71]
    Karwan, M.H. and R.L. Rardin (1976). “Surrogate Dual Multiplier Search Procedures in Integer Programming,” School of Industrial Systems Engineering, Report Series No. J-77-13, Georgia Institute of Technology.Google Scholar
  72. [72]
    Karwan, M.H. and R.L. Rardin (1979). “Some Relationships Between Lagrangean and Surrogate Duality in Integer Programming,” Mathematical Programming, 17, 230–334.CrossRefGoogle Scholar
  73. [73]
    Kelly, J.P., M. Laguna and F. Glover (1996). “Tabu Search and Scatter Search for Optimizing Simulation,” School of Business, University of Colorado, Presented at the national INFORMS Meeting, Washington, D.C.).Google Scholar
  74. [74]
    Kelly, J.P. and J. Xu (1995). “Tabu Search and Vocabulary Building for Routing Problems,” Graduate School of Business Administration, University of Colorado at Boulder.Google Scholar
  75. [75]
    Kincaid, R.K., (1995). “Actuator Placement for Active Sound and Vibration Control of Cylinders,” NASA ASEE Report.Google Scholar
  76. [76]
    Kincaid, R.K. and R.T. Berger (1993). “The Damper Placement Problem on Space Truss Structures,” Location Science, Vol. 1, No. 3, pp. 219–234.Google Scholar
  77. [77]
    Kincaid, R.K., A.D. Martin, and J.A. Hinkley (1995). “Heuristic Search for the Polymer Straightening Problem,” Computational Polymer Science, Vol. 5, pp. 1–5.Google Scholar
  78. [78]
    Laguna, M., J.P. Kelly, J.L. Gonzalez-Velarde and F. Glover (1995). “Tabu Search for the Multilevel Generalized Assignment Problem,” European Journal of Operations Research, 82, 176–189.CrossRefGoogle Scholar
  79. [79]
    Laguna M., R. Marti and V. Valls (1995). “Arc Crossing Minimization in Hierarchical Digraphs with Tabu Search,” Tech Report, Graduate School of Business, University of Colorado, Campus Box 419, Boulder, CO 80309.Google Scholar
  80. [80]
    Lee, P., A. Sartori, G. Tecchiolli and A. Zorat (1995). A Parallel Processor for Neural Networks,” 1995 Symposium on VLSI Circuits — Digest of Technical Papers, 8–10 June, 1995, Kyoto, IEEE CAT. No. 95 CE 35780, p. 81–82.Google Scholar
  81. [81]
    Løkketangen, A. and F. Glover (1996). “Surrogate Constraint Methods with Simple Learning for Satisfiability Problems,” Proceedings of the DI-MACS workshop on Satisfiability Problems: Theory and Applications, D-Z. Du, J. Gu and P. Pardalos, editors.Google Scholar
  82. [82]
    Løkketangen, A. and D. L. Woddruff, (1996). “Progressive Hedging and Tabu Search Applied to Mixed Integer (0,1) Multi-Stage Stochastic Programming,” Forthcoming in Journal of Heuristics.Google Scholar
  83. [83]
    Lopez, L., M.W. Carter and M. Gendreau (1996). “The Hot Strip Mill Production Scheduling Problem: A Tabu Search Approach,” Centre de recherche sur les transports, Universite de Montreal.Google Scholar
  84. [84]
    Marti, R. (1996). “An Aggressive Search Procedure for the Bipartite Drawing Problem,” In Meta-Heuristics: Theory & Applications, 97–113, I.H. Osman and J.P. Kelly (eds.), Kluwer Academic Publishers.Google Scholar
  85. [85]
    Martins, S.L., C.C. Ribeiro and N.R. Rodriguez (1996). “Parallel Programming Tools for Distributed Memory Environments,” (in Portuguese), Research report MCC-01/96, Department of Computer Science, Catholic University of Rio de Janeiro.Google Scholar
  86. [86]
    Mazzola, J.B. and R.H. Schantz (1995a). “Single-facility Resource Allocation Under Capacity-based Economies and Diseconomies of Scope,” Management Science, 41, 669–689.CrossRefGoogle Scholar
  87. [87]
    Mazzola, J.B. and R.H. Schantz (1995b). “Multiple-Facility Loading Under Capacity-Based Economies of Scope,” Working Paper, Fuqua School of Business, Duke University, August.Google Scholar
  88. [88]
    Mazzola, J.B., A.W. Neebe, and C.M. Rump (1995). “Multiproduct Production Planning in the Presence of Work-Force Learning,” Working Paper, Fuqua School of Business, Duke University, August.Google Scholar
  89. [89]
    Michalewicz, Z. and C. Janikow (1991). “Genetic Algorithms for Numerical Optimization,” Statistics and Computing, 1, 75–91.CrossRefGoogle Scholar
  90. [90]
    Mühlenbein, H., M. Gorges-Schleuter and O. Kremer (1988). “Evolution Algorithms in Combinatorial Optimization,” Parallel Computing, 7, 65–88.CrossRefGoogle Scholar
  91. [91]
    Mühlenbein, H. and D. Schlierkamp-Voosen (1994). “The Science of Breeding and its Application to the Breeder Genetic Algorithm,” Evolutionary Computation 1, 335–360.CrossRefGoogle Scholar
  92. [92]
    Mühlenbein, H. and H.-M. Voigt (1996). “Gene Pool Recombination in Genetic Algorithms,” In Meta-Heurisitics: Theory & Applications, Mühlenbein, H. and H.-M. Voigt, eds., 53–62, Kluwer Academic Publishers.Google Scholar
  93. [93]
    Mulvey, J. (1995). “Generating Scenarios for the Towers Perrin Investment Systems,” Technical Report SOR Report, Princeton University, Department of Civil Engineering and Operations Research, Princeton University, Princeton, NJ, to appear Interfaces.Google Scholar
  94. [94]
    Nowicki E. and Smutnicki C., (1993). “A Fast Taboo Search Algorithm for the Job Shop,” Report ICT PRE 8/93, Technical University of Wroclaw. Management Science. (in print), 1996.Google Scholar
  95. [95]
    Nowicki, E. and C. Smutnicki (1994). “A Fast Taboo Search Algorithm for the Flow Shop,” Report ICT PRE 8/94, Technical University of Wroclaw. European J. Oper. Res. (in print), 1996.Google Scholar
  96. [96]
    Nowicki, E. and C. Smutnicki (1995). “The Flow Shop with Parallel Machines: A Tabu Search Approach,” Report ICT PRE 30/95, Technical University of Wroclaw.Google Scholar
  97. [97]
    Pardalos, P.M., X. Liu and G. Xue (1995). “Protein Conformation of Lattice Using Tabu Search,” Unpublished.Google Scholar
  98. [98]
    Pesch, E. and F. Glover (1995). “TSP Ejection Chains,” Graduate School of Business, University of Colorado, Boulder, to appear in Discrete Applied Mathematics.Google Scholar
  99. [99]
    Porto, S.C.S. and C.C. Ribeiro (1995a). “A Tabu Search Approach to Task Scheduling on Heterogeneous Processors Under Precedence Constraints,” International Journal of High-Speed Computing 7, 45–71.CrossRefGoogle Scholar
  100. [100]
    Porto, S.C.S. and C.C. Ribeiro (1995b). “Parallel Tabu Search Message-passing Synchronous Strategies for Task Scheduling Under Precedence Constraints,” to appear in Journal of Heuristics.Google Scholar
  101. [101]
    Potvin, J. Y., T. Kervahut, B. L. Garcia and J. M. Rousseau (1996). “The Vehicle Routing Problem with Time Windows — Part I: Tabu Search,” INFORMS Journal on Computing Vol 8, No. 2, 158–164.CrossRefGoogle Scholar
  102. [102]
    Rego, C. (1996a). “Relaxed Tours and Path Ejections for the Traveling Salesman Problems,” Universidade Portucalense, Porto, Portugal.Google Scholar
  103. [103]
    Rego, C. (1996b). “A Subpath Ejection Method for the Vehicle Routing Problem,” Universidade Portucalense, Porto, Portugal.Google Scholar
  104. [104]
    Rego, C. and C. Roucairol (1996). “A Parallel Tabu Search Algorithm Using Ejection Chains for the Vehicle Routing Problem,” In Meta-Heuristics: Theory & Applications, 661–675, I.H. Osman and J.P. Kelly, (eds.), Kluwer Academic Publishers.Google Scholar
  105. [105]
    Rochat, Y. and F. Semet (1994). “A Tabu Search Approach for Delivering Pet Food and Flour in Switzerland,” J. Opl. Res. Soc., Vol 45, No. 11 1233–1246.Google Scholar
  106. [106]
    Rochat, Y. and E. Taillard (1995). “Probabilistic Diversification and Intensification in Local Search for Vehicle Routing,” Journal of Heuristics, Vol. 1, No. 1, 147–167.CrossRefGoogle Scholar
  107. [107]
    Rolland, E. (1995). “A Tabu Search Method for Constrained Real-Number Search: Applications to Portfolio Selection,” Working paper, The A. Gary Anderson Graduate School of Management, University of California, Riverside.Google Scholar
  108. [108]
    Rolland, E. and H. Johnson (1996). “Skewness and the Mean-Variance Frontier: A Tabu Search Approach,” Working paper, The A. Gary Anderson Graduate School of Management, University of California, Riverside.Google Scholar
  109. [109]
    Rolland, E., H. Pirkul and F. Glover (1995). “Tabu Search for Graph Partitioning,” in Annals of Operations Research, Special issue on Metaheuristics in Optimization.Google Scholar
  110. [110]
    Rolland, E., D.A. Schilling and J.R. Current (1996). “The P-Median Problem: Efficient Solutions using Tabu Search,” to appear in European Journal of Operational Research.Google Scholar
  111. [111]
    Skorin-Kapov, J. (1990). “Tabu Search Applied to the Quadratic Assignment Problem,” ORSA Journal on Computing, Vol. 2, No. 1, 33–45.CrossRefGoogle Scholar
  112. [112]
    Skorin-Kapov, J. (1994). “Extensions of a Tabu Search Adaptation to the Quadratic Assignment Problem,” Computers and Operations Research, 21 (8), 855–865.CrossRefGoogle Scholar
  113. [113]
    Skorin-Kapov, J. and J.-F. Labourdette (1995). “On Minimum Congestion in Logically Rearrangeable Multihop Lightwave Networks,” forthcoming in Journal of Heuristics.Google Scholar
  114. [114]
    Skorin-Kapov, D., J. Skorin-Kapov and M. O’Kelly (1995). “Tight Linear Programming Relaxations of p-Hub Median problems,” (forthcoming in) European Journal of Operational Research.Google Scholar
  115. [115]
    Skorin-Kapov, D. and J. Skorin-Kapov (1994). “On Tabu Search for the Location of Interacting Hub Facilities,” European Journal on Operational Research, 73 (3), 501–508.Google Scholar
  116. [116]
    Skorin-Kapov, J. and A. Vakharia (1993). “Scheduling a Flow-Line Manufacturing Cell: A Tabu Search Approach,” International Journal of Production Research, 31 (7), 1721–1734.CrossRefGoogle Scholar
  117. [117]
    Spears, W.M. and K.A. DeJong (1991). “On the Virtues of Uniform Crossover,” In 4th International Conference on Genetic Algorithms, La Jolla, CA.Google Scholar
  118. [118]
    Sun, M., J.E. Aronson, P.G. McKeown and D. Drinka (1995). “A Tabu Search Heuristic Procedure for the Fixed Charge Transportation Problem,” Working Paper No. 95–414, Terry College of Business, The University of Georgia, May.Google Scholar
  119. [119]
    Taillard, E., P. Badeau, M. Gendreau, F. Guertin and J-Y. Potvin (1995). “A New Neighborhood Structure for the Vehicle Routing Problem with Time Windows,” Centre de Recherche sur les Transports, Publication CRT-95–66.Google Scholar
  120. [120]
    Taillard, E. (1993). “Parallel Iterative Search Methods for Vehicle Routing Problems,” Networks, Vol. 23, 661–673.CrossRefGoogle Scholar
  121. [121]
    Trafalis, T., and I. Al-Harkan (1995). “A Continuous Scatter Search Approach for Global Optimization,” Extended Abstract in: Conference in Applied Mathematical Programming and Modeling (APMOD’95), London, UK, 1995.Google Scholar
  122. [122]
    Toulouse, Michael, Teodor G. Crainic and Michel Gendreau (1996). “Communication Issues in Designing Cooperative Multi-Thread Parallel Searchers” In Meta- Heuristics: Theory & Applications, pp. 503–522, I. H. Osman and J.P. Kelly (eds.), Kluwer Academic Publishers.Google Scholar
  123. [123]
    Ulder, N.L.J., E. Pech, P.J.M. van Laarhoven, H.J. Bandelt and E.H.L. Aarts (1991). “Genetic Local Search Algorithm for the Traveling Salesman Problem,” In Parallel Problem Solving from Nature, eds. R. Maenner and H.P. Schwefel, pp. 109–116. Springer-Verlag, Berlin.Google Scholar
  124. [124]
    Vaessens, R.J.M, E.H.L. Aarts and J.K. Lenstra (1995). “Job Shop Scheduling by Local Search,” Memorandum COSOR 94-05, Eidhoven University of Technology.Google Scholar
  125. [125]
    Valls V., R. Marti and P. Lino (1995). “A Tabu Thresholding Algorithm for Arc Crossing Minimization in Bipartite Graphs,” Annals of Operations Research, Vol. 60, Metaheuristics in Combinatorial Optimization.Google Scholar
  126. [126]
    Voss, S. (1992). “Network Design Formulations in Schedule Synchronization,” Lecture Notes in Economics and Mathematical Systems, 386, 137–152.CrossRefGoogle Scholar
  127. [127]
    Voss, S. (1993). “Tabu Search: Applications and Prospects,” In: D.-Z. Du und P.M. Pardalos (Hrsg.), Network Optimization Problems: Algorithms, Applications and Complexity, World Scientific, Singapore, 333–353.Google Scholar
  128. [128]
    Voss, S. (1994). “Concepts for Parallel Tabu Search,” Technische Hochschule Dormstadt, Germany.Google Scholar
  129. [129]
    Whitley, D., V.S. Gordon and K. Mathias (1994). “Lamarckian Evolution, the Baldwin Effect and Function Optimization,” in Proceedings of the Parallel Problem Solving from Nature, 3, pp. 6–15. New York: Springer-Verlag.Google Scholar
  130. [130]
    Whitley, D. (1993). Foundations of Genetic Algorithms 2,Morgan Kaufmann.Google Scholar
  131. [131]
    Woodruff, D. (1996). “Proposals for Chunking and Tabu Search,” Submitted to European Journal of Operational Research.Google Scholar
  132. [132]
    Wright, A.H. (1990). “Genetic Algorithms for Real Parameter Optimization,” In Foundations of Genetic Algorithms, ed. G. Rawlins, pp. 205–218. Morgan Kaufmann, Los Altos, CA.Google Scholar
  133. [133]
    Zenios, S. (1996). “Dynamic Financial Modeling and Optimizing the Design of Financial Products,” Presented at the National INFORMS Meeting, Washington, D.C., May 1996.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Fred Glover
    • 1
  1. 1.College of BusinessUniversity of ColoradoBoulderUSA

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