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ε-Optimality for bicriteria programs and its application to minimum cost flows

ε-Optimalität für bikriterielle Programme und Anwendung auf kostenminimale Flüsse

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Abstract

A subsetSX of feasible solutions of a multicriteria optimization problem is called ε-optimal w.r.t. a vector-valued functionf:X→Y \( \subseteq \)K if for allxX there is a solutionz xS so thatf k(z x)≤(1+ε)f k (x) for allk=1,...,K. For a given accuracy ε>0, a pseudopolynomial approximation algorithm for bicriteria linear programming using the lower and upper approximation of the optimal value function is given. Numerical results for the bicriteria minimum cost flow problem on NETGEN-generated examples are presented.

Zusammenfassung

Eine TeilmengeSX von zulässigen Lösungen eines multikriteriellen Optimierungsproblems heißt ε-optimal bezüglich einer vektorwertigen Funktionf:f:X→ℝK, wenn für jedesxX eine Lösungz xS existiert, so daßf k(z x)≤(1+ε)f k (x) für allek=1, …,K gilt. Es wird ein pseudopolynomialer Algorithmus vorgestellt, der mit Hilfe einer oberen und unteren Approximation die Kurve der effizienten Punkte eines bikriteriellen linearen Programms mit einer vorgegebenen Genauigkeit ε>0 approximiert. Ergebnisse numerischer Untersuchungen mit dem bikriteriellen Kostenfluß Problem anhand von NETGEN-Netzwerken werden präsentiert.

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References

  1. Bertsekas, D. P., Tseng, P.: The Relax Codes for Linear Minimum Cost Network Flow Problems. Annals of Operations Research13, 125–190 (1988).

    Google Scholar 

  2. Blaschke, W.: Analytische Geometrie. Birkhäuser Verlag. Basel, Stuttgart (1954).

    Google Scholar 

  3. Burkard, R. E., Hamacher, H., Rote, G.: Approximation of Convex Functions and Applications in Mathematical Programming. Report 89-1987, Institut für Mathematik, Technische Universität Graz (1987).

  4. Fruhwirth, B., Burkard, R. E., Rote, G.: Approximation of Convex Curves with Applications to the Bicriterial Minimum Cost Flow Problem. European J. of Oper. Res.42, 326–338 (1989).

    Google Scholar 

  5. Grigoriadis, M. D.: An efficient implementation of the network simplex method. Mathematical Programming Study26, 83–111 (1986).

    Google Scholar 

  6. Klingman, D., Napier, K., and Stutz, J.: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Problems. Management Science20, 814–821 (1974).

    Google Scholar 

  7. Orlin, J. B.: A Faster Strongly Polynomial Minimum Cost Flow Algorithm. Proc. 20th ACM Symp. on the Theory of Comp., 377–387 (1988).

  8. Rote, G.: The Convergence Rate of the Dandwich Algorithm for Approximating Convex Functions. Report 118-1988, Institut für Mathematik, Technische Universität Graz (1989).

  9. Ruhe, G.: Flüsse in Netzwerken—Komplexität und Algorithmen. Dissertation B, Technische Hochschule Leipzig, Sektion Mathematik und Informatik. (1988).

  10. Ruhe, G.: Complexity Results for Multicriterial and Parametric Networks Flows Using a Pathological Graph of Zadeh. Zeitschrift für Operations Research, Series A: Theory32, 9–27 (1988).

    Google Scholar 

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Partial support by the agreement on scientific and technical cooperation between GDR and Austria, Project A5.2, is gratefully acknowledged.

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Ruhe, G., Fruhwirth, B. ε-Optimality for bicriteria programs and its application to minimum cost flows. Computing 44, 21–34 (1990). https://doi.org/10.1007/BF02247962

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