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New results on the equivalence between zero-one programming and continuous concave programming

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Abstract

In this work, we study continuous reformulations of zero-one concave programming problems. We introduce new concave penalty functions and we prove, using general equivalence results here derived, that the obtained continuous problems are equivalent to the original combinatorial problem.

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References

  1. Abello J., Butenko S., Pardalos P.M., Resende M.: Finding independent sets in a graph using continuous multivariable polynomial formulations. J. Glob. Optim. 21, 111–137 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  2. Balasundaram B., Butenko S.: Constructing test functions for global optimization using continuous formulations of graph problems. Optim. Methods Softw. 20, 439–452 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  3. Borchardt M.: An exact penalty approach for solving a class of minimization problems with Boolean variables. Optim. 19(6), 829–838 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  4. Giannessi F., Niccolucci F.: Connections between nonlinear and integer programming problems. Symp. Math. 19, 161–176 (1976)

    MathSciNet  Google Scholar 

  5. Horst, R., Pardalos, P.M., Thoai, N.V.: Introduction to Global Optimization, 2nd edn. Kluwer, Dordrecht (2000)

  6. Kalantari B., Rosen J.B.: Penalty formulation for zero-one integer equivalent problem. Math. Program. 24, 229–232 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  7. Kalantari B., Rosen J.B.: Penalty formulation for zero-one nonlinear programming. Discrete Appl. Math. 16(2), 179–182 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  8. Mangasarian O.L.: Machine learning via polyhedral concave minimization. In: Fischer, H., Riedmueller, B., Schaeffler, S. (eds) Applied Mathematics and Parallel Computing—Festschrift for Klaus Ritter, pp. 175–188. Physica-Verlag, Germany (1996)

    Google Scholar 

  9. Mangasarian, O.L.: Knapsack Feasibility as an Absolute Value Equation Solvable by Successive Linear Programming. Data Mining Institute Technical Report 08-03, September 2008. Optimization Letters (2008, to appear)

  10. Pardalos P.M., Rosen J.B.: Constrained Global Optimization: algorithms and Applications. Lecture Notes in Computer Science, vol. 268. Springer, Berlin (1987)

    Book  Google Scholar 

  11. Pardalos P.M., Prokopyev O.A., Busygin S.: Continuous Approaches for Solving Discrete Optimization Problems. Handbook on Modelling for Discrete Optimization, vol. 8, pp. 39–60. Springer, New York (2006)

    Google Scholar 

  12. Raghavachari M.: On connections between zero-one integer programming and concave programming under linear constraints. Oper. Res. 17(4), 680–684 (1969)

    Article  MATH  MathSciNet  Google Scholar 

  13. Rinaldi, F., Schoen, F., Sciandrone, M.: Concave programming for minimizing the zero-norm over polyhedral sets. Technical report RT 2/2008, Dipartimento Sistemi e Informatica, Università di Firenze. Computational Optimization and Applications (2008, to appear)

  14. Rockafellar T.: Convex Analysis. Princeton University Press, Princeton (1970)

    MATH  Google Scholar 

  15. Zhu W.X.: Penalty parameter for linearly constrained 0–1 quadratic programming. J. Optim. Theory Appl. 116(1), 229–239 (2003)

    Article  MATH  MathSciNet  Google Scholar 

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Correspondence to Francesco Rinaldi.

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Rinaldi, F. New results on the equivalence between zero-one programming and continuous concave programming. Optim Lett 3, 377–386 (2009). https://doi.org/10.1007/s11590-009-0117-x

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