Skip to main content
Log in

An Approach to the Subproblem of the Cutting Angle Method of Global Optimization

  • Published:
Journal of Global Optimization Aims and scope Submit manuscript

Abstract

The solution of the Subproblem of the Cutting Angle Method of Global Optimization for problems of minimizing increasing positively homogeneous of degree one functions is proved to be NP-Complete. For the proof of this fact we formulate another problem which we call “Dominating Subset with Minimal Weight”. This problem is also NP-Complete. An O(n2)-time algorithm is presented for approximate solution of Dominant Subset with Minimal Weight Problem. This problem can be expressed as a kind of Assignment Problem in which it is allowed to assign multiple tasks to a single processor. Experimental analysis of the algorithm is performed using the program implemented in ANSI-C. The results of the analysis show the efficiency of the proposed algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Andramonov, M.Yu., Rubinov, A.M. and Glover B.M. (1997), Cutting Angle methods for minimizing increasing convex along rays functions. Research Report 97/7, SITMS, University of Ballarat.

  2. M.Yu. Andramonov A.M. Rubinov B.M. Glover (1999) ArticleTitleCutting Angle methods in Global Optimization Applied Mathematics Letters 12 95–100 Occurrence Handle10.1016/S0893-9659(98)00179-7

    Article  Google Scholar 

  3. Babayev, Dj.A. (2000), An exact method for solving the subproblem of the cutting angle method of global optimization. In: Optimization and Related Topics, in Kluwer Academic Publishers, ser. ‘Applied Optimization’, Dordrecht, Vol. 47, pp. 15–26.

  4. A.M. Bagirov A.M. Rubinov (2000) ArticleTitleGlobal minimization of increasing positively homogeneous functions over the unit simplex Annals of Operation Research 98 171–187 Occurrence Handle10.1023/A:1019204407420

    Article  Google Scholar 

  5. A.M. Bagirov A.M. Rubinov (2001) Modified versions of the cutting angle method N. Hadjisavvas P.M. Pardalos (Eds) Nonconvex Optimization and Its Applications Advances in Convex Analysis and Global Optimization Kluwer Academic Publishers Dordrecht

    Google Scholar 

  6. A.M. Bagirov A.M. Rubinov (2003) ArticleTitleCutting angle method and a local search Journal of Global Optimization 27 193–213 Occurrence Handle10.1023/A:1024858200805

    Article  Google Scholar 

  7. R.M. Garey D.S. Johnson (1979) Computers and Intractability: A Guide to the Theory of NP-Completeness W.H. Freeman and Company New York NY

    Google Scholar 

  8. R. Horst P.M. Pardalos N.V. Thoai (2000) Introduction to Global Optimization, Nonconvex Optimization and its Applications Kluwer Academic Publishers Dordrecht

    Google Scholar 

  9. S. Martello P. Toth (1990) Knapsack Problems: Algorithms and Computer Implementations John Wiley and Sons Chichester

    Google Scholar 

  10. A.M. Rubinov (2000) Abstract Convexity and Global Optimization Kluwer Academic Publishers Dordrecht

    Google Scholar 

  11. A.M. Rubinov M.Yu. Andramonov (1999) ArticleTitleMinimizing increasing star-shaped functions based on abstract convexity Journal of Global Optimization 15 19–39 Occurrence Handle10.1023/A:1008344317743

    Article  Google Scholar 

  12. A.M. Rubinov M. Yu. Andramonov (1999) ArticleTitleLipshitz programming via increasing convex along rays functions Optimization Methods and Software 10 763–781

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Urfat G. Nuriyev.

Additional information

Mathematics Subject Classification (2000): 65K05, 90C27, 68Q25

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nuriyev, U.G. An Approach to the Subproblem of the Cutting Angle Method of Global Optimization. J Glob Optim 31, 353–370 (2005). https://doi.org/10.1007/s10898-004-1687-x

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10898-004-1687-x

Keywords

Navigation