Performance Guarantees of Local Search for Multiprocessor Scheduling

  • Petra Schuurman
  • Tjark Vredeveld
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2081)

Abstract

This paper deals with the worst-case performance of local search algorithms for makespan minimization on parallel machines. We analyze the quality of the local optima obtained by iterative improvements over the jump, the swap, and the newly defined push neighborhood.

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References

  1. 1.
    P. Brucker, J. Hurink, and F. Werner. Improving local search heuristics for some scheduling problems I. Discrete Applied Mathematics, 65:97–122, 1996.MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    P. Brucker, J. Hurink, and F. Werner. Improving local search heuristics for some scheduling problems II. Discrete Applied Mathematics, 72:47–69, 1997.MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Y. Cho and S. Sahni. Bounds for list schedules on uniform processors. SIAM Journal on Computing, 9:511–522, 1980.CrossRefMathSciNetGoogle Scholar
  4. 4.
    U. Feige, M. Karpinski, and M. Langberg. Improved approximation of MAX-CUT on graphs of bounded degree. Technical Report 85215 CS, Institut för Informatik, Universität Bonn, 2000.Google Scholar
  5. 5.
    M.R. Garey and D.S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, San Francisco, 1979.MATHGoogle Scholar
  6. 6.
    M.X. Goemans and D.P. Williamson. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. Journal of the ACM, 42:1115–1145, 1995.MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    R.L. Graham, E.L. Lawler, J.K. Lenstra, and A.H.G. Rinnooy Kan. Optimization and approximation in deterministic sequencing and scheduling: a survey. Annals of Discrete Mathematics, 5:287–326, 1979.MATHMathSciNetCrossRefGoogle Scholar
  8. 8.
    D.S. Hochbaum and D.B. Shmoys. Using dual approximation algorithms for scheduling problems: theoretical and practical results. Journal of the ACM, 34:144–162, 1987.CrossRefMathSciNetGoogle Scholar
  9. 9.
    D.S. Hochbaum and D.B. Shmoys. A polynomial approximation scheme for machine scheduling on uniform processors: using the dual approximation approach. SIAM Journal on Computing, 17:539–551, 1988.MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    B.W. Kernighan and S. Lin. An efficient heuristic procedure for partitioning graphs. The Bell System Technical Journal, 49:291–307, 1970.Google Scholar
  11. 11.
    M.R. Korupolu, C.G. Plaxton, and R. Rajaraman. Analysis of a local search heuristic for facility location problems. Technical Report 98-30, DIMACS, 1998.Google Scholar
  12. 12.
    J.K. Lenstra, D.B. Shmoys, and É. Tardos. Approximation algorithms for scheduling unrelated parallel machines. Mathematical Programming, 46:259–271, 1990.MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    S. Lin and B.W. Kernighan. An effective heuristic for the traveling salesman problem. Operations Research, 21:489–516, 1973.MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Petra Schuurman
    • 1
  • Tjark Vredeveld
    • 1
  1. 1.Department of Mathematics and Computing ScienceTechnische Universiteit EindhovenThe Netherlands

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