Optimization Letters

, Volume 1, Issue 3, pp 213–225 | Cite as

Heuristic for a new multiobjective scheduling problem

  • Anne Setämaa-Kärkkäinen
  • Kaisa Miettinen
  • Jarkko Vuori
Original Paper

Abstract

We consider a telecommunication problem in which the objective is to schedule data transmission to be as fast and as cheap as possible. The main characteristic and restriction in solving this multiobjective optimization problem is the very limited computational capacity available. We describe a simple but efficient local search heuristic to solve this problem and provide some encouraging numerical test results. They demonstrate that we can develop a computationally inexpensive heuristic without sacrificing too much in the solution quality.

Keywords

Heuristics Parallel machine scheduling Biobjective optimization Combinatorial optimization Telecommunications 

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References

  1. 1.
    Błażewicz J. (1987) Selected topics in scheduling theory. In: Martello S., Laporte G., Minoux M., Ribeiro C. (eds) Surveys in Combinatorial Optimization, vol 31 of Annals of Discrete Mathematics. Elsevier, Amsterdam, p. 1–59Google Scholar
  2. 2.
    Cormen T.H., Leiserson C.E., Rivest R.L. (1990) Introduction to Algorithms. The MIT Press and McGraw-Hill Book Company, New YorkGoogle Scholar
  3. 3.
    Ehrgott M., Tenfelde-Podehl D. (2003) Computation of ideal and Nadir values and implications for their use in MCDM methods. Eur. J. Operat. Res. 151(1): 119–139MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Graham R.L., Lawler E.L., Lenstra J.K., Rinnooy Kan A.H.G. (1979) Optimization and approximation in deterministic sequencing and scheduling: a survey. In: Hammer P.L., Johnson E.L., Korte B.H. (eds) Discrete optimization II, vol 5 of Annals of Discrete Mathematics. North-Holland Publishing Company, Amsterdam, pp. 287–326Google Scholar
  5. 5.
    Gustafsson E., Jonsson A. (2003) Always best connected. IEEE Wirel. Commun. 10(1): 49–55CrossRefGoogle Scholar
  6. 6.
    Hall L.A. (1997) Approximation algorithms for scheduling. In: Hochbaum D.S. (ed) Approximation Algorithms for NP-hard Problems. PWS Publishing Company, BostonGoogle Scholar
  7. 7.
    ILOG CPLEX 8.0 User’s Manual. ILOG, (2002)Google Scholar
  8. 8.
    Intel XScale Microarchitecture, Technical Summary. Intel Corporation, (2000)Google Scholar
  9. 9.
    Jansen K., Porkolab L. (2001) Improved approximation schemes for scheduling unrelated parallel machines. Math. Oper. Res. 26(2): 324–338MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Korte B., Vygen J. (2002) Combinatorial Optimization: Theory and Algorithms. Springer, Berlin Heidelberg New YorkMATHGoogle Scholar
  11. 11.
    Miettinen K. (1999) Nonlinear Multiobjective Optimization. Kluwer, DordrechtMATHGoogle Scholar
  12. 12.
    Miettinen K., Mäkelä, M.M., Kaario K.: Experiments with classification-based scalarizing functions in interactive multiobjective optimization. Eur. J. Oper. Res. (2006) (to appear)Google Scholar
  13. 13.
    Nagar A., Haddock J., Heragu S. (1995) Multiple and bicriteria scheduling: a literature survey. Eur. J. Oper. Res. 81(1): 88–104MATHCrossRefGoogle Scholar
  14. 14.
    Setämaa-Kärkkäinen A., Miettinen K., Vuori J. (2006) Best compromise solution for a new multiobjective scheduling problem. Comput. Oper. Res. 33(8): 2353–2368MATHCrossRefGoogle Scholar
  15. 15.
    T’Kindt V., Billaut J.-C. (2002) Multicriteria scheduling problems. In: Ehrgott M., Gandibleux X. (eds) Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys. Kluwer, Dordrecht, pp. 445–491Google Scholar
  16. 16.
    T’kindt V., Billaut J.-C. (2002) Multicriteria Scheduling: Theory, Models and Algorithms. Springer, Berlin Heidelberg New YorkMATHGoogle Scholar
  17. 17.
    Trick M.A. (1994) Scheduling multiple variable-speed machines. Oper. Res. 42(2): 234–248MATHCrossRefGoogle Scholar
  18. 18.
    Varshney U., Jain R. (2001) Issues in emerging 4G wireless networks. IEEE Comput. 34(6): 94–96Google Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Anne Setämaa-Kärkkäinen
    • 1
  • Kaisa Miettinen
    • 2
  • Jarkko Vuori
    • 3
  1. 1.Department of Mathematical Information TechnologyUniversity of JyväskyläJyväskyläFinland
  2. 2.Helsinki School of EconomicsHelsinkiFinland
  3. 3.EVTEK University of Applied SciencesEspooFinland

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