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On reduction of duality gap in quadratic knapsack problems

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Abstract

We investigate in this paper the duality gap between quadratic knapsack problem and its Lagrangian dual or semidefinite programming relaxation. We characterize the duality gap by a distance measure from set {0, 1}n to certain polyhedral set and demonstrate that the duality gap can be reduced by an amount proportional to the square of the distance. We further discuss how to compute the distance measure via cell enumeration method and to derive the corresponding improved upper bound of the problem.

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References

  1. Allemand K., Fukuda K., Liebling T.M., Steiner E.: A polynomial case of unconstrained zero-one quadratic optimization. Math. Program. 91, 49–52 (2001)

    Google Scholar 

  2. Avis D., Fukuda K.: Reverse search for enumeration. Discret. Appl. Math. 65, 21–46 (1996)

    Article  Google Scholar 

  3. Billionnet A., Faye A., Soutif E.: A new upper bound for the 0–1 quadratic knapsack problem. Eur. J. Oper. Res. 112, 664–672 (1999)

    Article  Google Scholar 

  4. Billionnet A., Soutif E.: An exact method based on Lagrangian decomposition for the 0–1 quadratic knapsack problem. Eur. J. Oper. Res. 157, 565–575 (2004)

    Article  Google Scholar 

  5. Caprara A., Pisinger D., Toth P.: Exact solution of the quadratic knapsack problem. INFORMS J. Comput. 11, 125–139 (1999)

    Article  Google Scholar 

  6. Chaillou P., Hansen P., Mahieu Y.: Best network flow bounds for the quadratic knapsack problem. Lect. Notes Math. 1403, 226–235 (1986)

    Google Scholar 

  7. Fang S.C., Gao D.Y., Sheu R.L., Wu S.Y.: Canonical dual approach to solve 0–1 quadratic programming problems. J. Ind. Manag. Optim. 4, 125–142 (2008)

    Article  Google Scholar 

  8. Ferrez J.A., Fukuda K., Liebling T.M.: Solving the fixed rank convex quadratic maximization in binary variables by a parallel zonotope construction algorithm. Eur. J. Oper. Res. 166, 35–50 (2005)

    Article  Google Scholar 

  9. Gallo G., Hammer P.L., Simeone B.: Quadratic knapsack problems. Math. Program. Study 12, 132–149 (1980)

    Article  Google Scholar 

  10. Gallo G., Simeone B.: On the supermodular knapsack problems. Math. Program. 45, 295–309 (1988)

    Article  Google Scholar 

  11. Gao D.Y., Ruan N., Sherali H.D.: Solutions and optimality criteria for nonconvex constrained global optimization problems with connections between canonical and Lagrangian duality. J. Glob. Optim. 45, 473–497 (2009)

    Article  Google Scholar 

  12. Hammer P.L. Jr, Rader D.J.: Efficient methods for solving quadratic 0–1 knapsack problems. INFOR 35, 170–182 (1997)

    Google Scholar 

  13. Helmberg, C.: Semidefinite programming for combinatorial optimization. Technical report, Konrad-Zuse-Zentrum, Berlin. ZIB-Report ZR-00-34. ftp://ftp.zib.de/pub/zib-publications/reports/ZR-00-34.pdf. (2000)

  14. Helmberg C., Rendl F., Weismantel R.: Quadratic knapsack relaxations using cutting planes and semidefinite programming. Integer Programming and Combinatorial Optimization. Lect. Notes Comput. Sci. 1084, 175–189 (1996)

    Article  Google Scholar 

  15. Helmberg C., Rendl F., Weismantel R.: A semidefinite programming approach to the quadratic knapsack problem. J. Comb. Optim. 4, 197–215 (2000)

    Article  Google Scholar 

  16. Laurent M., Rendl F.: Semidefinite programming and integer programming. In: Aardal, K., Nemhauser, G., Weismantel, R. (eds) Discrete Optimization, pp. 393–514. Elsevier, Amsterdam (2005)

    Chapter  Google Scholar 

  17. Li D., Sun X.L.: Nonlinear Integer Programming. Springer, New York (2006)

    Google Scholar 

  18. Michelon P., Veilleux L.: Lagrangian methods for the 0–1 quadratic knapsack problem. Eur. J. Oper. Res. 92, 326–341 (1996)

    Article  Google Scholar 

  19. Nesterov Y., Nemirovskii A.: Interior-Point Polynomial Algorithms in Convex Programming. SIAM, Philadelphia, PA (1994)

    Book  Google Scholar 

  20. Pisinger D.: The quadratic knapsack problem–a survey. Discret. Appl. Math. 155, 623–648 (2007)

    Article  Google Scholar 

  21. Sleumer N.: Output-sensitive cell enumeration in hyperplane arrangements. Nord. J. Comput. 6, 137–161 (1999)

    Google Scholar 

  22. Wang Z.B., Fang S.C., Gao D.Y., Xing W.X.: Global extremal conditions for multi-integer quadratic programming. J. Ind. Manag. Optim. 4, 213–225 (2008)

    Article  Google Scholar 

  23. Zaslavsky T.: Facing up to arrangements: face-count formulas for partitions of space by hyperplanes. Mem. Am. Math. Soc. 1, 1–101 (1975)

    Google Scholar 

  24. Zheng, X.J.: Studies on the Theory and Methods for Continuous and Integer Nonconvex Quadratic Programming Problems. PhD thesis, Shanghai University, Shanghai, China (2009)

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Zheng, X.J., Sun, X.L., Li, D. et al. On reduction of duality gap in quadratic knapsack problems. J Glob Optim 54, 325–339 (2012). https://doi.org/10.1007/s10898-012-9872-9

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  • DOI: https://doi.org/10.1007/s10898-012-9872-9

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