Abstract
In this article we study thetabu search (TS) method in an application for solving an important class of scheduling problems. Tabu search is characterized by integrating artificial intelligence and optimization principles, with particular emphasis on exploiting flexible memory structures, to yield a highly effective solution procedure. We first discuss the problem of minimizing the sum of the setup costs and linear delay penalties when N jobs, arriving at time zero, are to be scheduled for sequential processing on a continuously available machine. A prototype TS method is developed for this problem using the common approach of exchanging the position of two jobs to transform one schedule into another. A more powerful method is then developed that employs insert moves in combination with swap moves to search the solution space. This method and the best parameters found for it during the preliminary experimentation with the prototype procedure are used to obtain solutions to a more complex problem that considers setup times in addition to setup costs. In this case, our procedure succeeded in finding optimal solutions to all problems for which these solutions are known and a better solution to a larger problem for which optimizing procedures exceeded a specified time limit (branch and bound) or reached a memory overflow (branch and bound/dynamic programming) before normal termination. These experiments confirm not only the effectiveness but also the robustness of the TS method, in terms of the solution quality obtained with a common set of parameter choices for two related but different problems.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
S.E. Elmaghraby and S.H. Park, “Scheduling jobs on a number of identical machines,AIIE Trans., vol. 16, no. 1, pp. 1–13, March 1974.
J.W. Barnes and L.K. Vanston, “Scheduling jobs with linear delay penalties and sequence dependent setup costs,”Operations Res., vol. 29, no. 1, pp. 146–160, January–February 1981.
T.L. Morin and R.F. Marsten, “Branch-and-bound strategies for dynamic programming,”Operations Res., vol. 24, no. 4, pp. 611–627, July–August 1976.
D. de Werra and A. Hertz, “Tabu search techniques: A tutorial and an application to neural networks,OR Spectrum, vol. 11, pp. 131–141, 1989.
F. Glover, “Tabu search: A tutorial,”Interfaces, vol. 20, no. 4, pp. 74–94, July–August 1990.
F. Glover and M. Laguna, “Tabu search,” inModern Heuristics for Combinatorial Optimization, C.R. Reeves (Ed.), Blackwell Scientific Publications, Oxford, 1993.
A. Hertz and D. de Werra, “Using tabu search techniques for graph coloring,”Computing, vol. 29, pp. 345–351, 1987.
F. Glover, E. Taillard, and D. de Werra, “A user's guide to tabu search,”Ann. Operations Res. (in press).
I.H. Osman, “Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem,Ann. Operations Res. (in press).
J. Chakrapani and J. Skorin-Kapov, “Massively parallel tabu search for the quadratic assignment problem,”Ann. Operations Res. (in press).
M. Widmer and A. Hertz, “A new method for the flow sequencing problem,”Eur. J. Operations Res., vol. 41, pp. 186–193, 1989.
L.K. Vanston, “A hybrid dynamic programming/branch-and-bound algorithm to solve multiple-machine scheduling problems,” Ph.D. Dissertation, Mechanical Engineering Department, The University of Texas at Austin, 1979.
T.A. Feo and M.G.C. Resende, “A probabilistic heuristic for a computationally difficult set covering problem,”Operations Res. Lett., vol. 8, pp. 67–71, 1989.
M. Laguna, J.W. Barnes, and F. Glover, “Tabu search methods for a single machine scheduling problem,”J. Intell. Manufact., vol. 2, pp. 63–74, 1991.
S.K. Gupta and J. Kyparisis, “Single machine scheduling research,”OMEGA Int. J. Mgmt. Sci., vol. 15, no. 3, pp. 207–227, 1987.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Laguna, M., Barnes, J.W. & Glover, F. Intelligent scheduling with tabu search: An application to jobs with linear delay penalties and sequence-dependent setup costs and times. Appl Intell 3, 159–172 (1993). https://doi.org/10.1007/BF00871895
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF00871895