Skip to main content
Log in

CHESS—Changing Horizon Efficient Set Search: A Simple Principle for Multiobjective Optimization

  • Published:
Journal of Heuristics Aims and scope Submit manuscript

Abstract

This paper presents a new concept for generating approximations to the non-dominated set in multiobjective optimization problems. The approximation set A is constructed by solving several single-objective minimization problems in which a particular function D(A, z) is minimized. A new algorithm to calculate D(A, z) is proposed.

No general approach is available to solve the one-dimensional optimization problems, but metaheuristics based on local search procedures are used instead. Tests with multiobjective combinatorial problems whose non-dominated sets are known confirm that CHESS can be used to approximate the non-dominated set. Straightforward parallelization of the CHESS approach is illustrated with examples.

The algorithm to calculate D(A, z) can be used in any other applications that need to determine Tchebycheff distances between a point and a dominant-free set.

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

  • Borges, P. Castro and M. Pilegaard Hansen. (1998). “ABasis for Future Successes in Multiobjective Combinatorial Optimization. ” IMM Technical Report, IMM-REP-1998–8, pp. 1–15.

  • Burkard, R., S. Karisch, and F. Rendl. (1997). “QAPLIB-A Quadratic Assignment Problem Library. ” Journal of Global Optimization 10, 391–403.

    Google Scholar 

  • Czyzak, P. and A. Jaszkiewicz. (1998). “Pareto Simulated Annealing-A Metaheuristic Technique for Multiple-objective Combinatorial Optimization. ” Journal of Multi-criteria Decision Analysis 7, 34–47.

    Google Scholar 

  • Habenicht, W. (1982). “Quad Trees, A Datastructure for Discrete Vector Optimization Problems. ” Lecture notes in Economics and Systems 209, 136–145.

    Google Scholar 

  • Hansen, M. Pilegaard. (1997). “Tabu Search for Multiobjective Optimization: Mots. ” Presented at the 13th MCDM Conference, Cape Town, South Africa.

  • Osman, I.H. and G. Laporte. (1996). “Metaheuristics: A Bibliography. ” Annals of Operations Research 63, 513–623.

    Google Scholar 

  • Paulli, J. (1993). “A Computational Comparison of Simulated Annealing and Tabu Search Applied to the Quadratic Assignment Problem. ” In René V.V. Vidal (ed.), Applied Simulated Annealing. Springer-Verlag, Lecture Notes in Economics and Mathematical Systems. pp. 85–102.

  • Pirlot, M. and R.V.V. Vidal. (1996). “Simulated Annealing: A Tutorial. ” Control and Cybernetics 25, 9–32.

    Google Scholar 

  • Serafini, P. (1987). “Some Considerations about Computational Complexity for Multi Objective Combinatorial Problems. ” In J. Jahn andW. Krabs (eds.), Recent Advances and Historical Development of Vector Optimization, Springer-Verlag, pp. 222–232. Lecture Notes in Economics and Mathematical Systems, vol. 294.

  • Sun, M. and R. E. Steuer. (1996). “InterQuad: An Interactive Quad Tree Based Procedure for Solving the Discrete Alternative Multiple Criteria Problem. ” European Journal of Operational Research 89, 462–472.

    Google Scholar 

  • Ulungu, E.L. and J. Teghem. (1994). “Multi-objective Combinatorial Optimization Problems: A Survey. ” Journal of Multi-criteria Decision Analysis 3, 83–104.

    Google Scholar 

  • Wierzbicki, A.P. (1979). “The Use of Reference Objectives in Multiobjective Optimization. ” LNEMS, 177, 468–486.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Borges, P.C. CHESS—Changing Horizon Efficient Set Search: A Simple Principle for Multiobjective Optimization. Journal of Heuristics 6, 405–418 (2000). https://doi.org/10.1023/A:1009638700683

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009638700683

Navigation