IDEAS home Printed from https://ideas.repec.org/p/aeg/report/2013-05.html
   My bibliography  Save this paper

A new class of functions for measuring solution integrality in the Feasibility Pump approach: Complete Results

Author

Listed:
  • Marianna De Santis

    (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza")

  • Stefano Lucidi

    (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza")

  • Francesco Rinaldi

    (Universita' di Padova Dipartimento di Matematica)

Abstract

Mixed-Integer optimization is a powerful tool for modeling many optimization problems arising from real-world applications. Finding a first feasible solution represents the first step for several MIP solvers. The Feasibility pump is a heuristic for finding feasible solutions to mixed integer linear problems which is effective even when dealing with hard MIP instances. In this work, we start by interpreting the Feasibility Pump as a Frank-Wolfe method applied to a nonsmooth concave merit function. Then, we define a general class of functions that can be included in the Feasibility Pump scheme for measuring solution integrality and we identify some merit functions belonging to this class. We further extend our approach by dynamically combining two different merit functions. Finally, we define a new version of the Feasibility Pump algorithm, which includes the original version of the Feasibility Pump as a special case, and we present computational results on binary MILP problems showing the effectiveness of our approach.

Suggested Citation

  • Marianna De Santis & Stefano Lucidi & Francesco Rinaldi, 2013. "A new class of functions for measuring solution integrality in the Feasibility Pump approach: Complete Results," DIAG Technical Reports 2013-05, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    • Handle: RePEc:aeg:report:2013-05
    as

    Download full text from publisher

    File URL: http://www.dis.uniroma1.it/~bibdis/RePEc/aeg/report/2013-05.pdf
    File Function: Revised version, 2013
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert M. Saltzman & Frederick S. Hillier, 1992. "A Heuristic Ceiling Point Algorithm for General Integer Linear Programming," Management Science, INFORMS, vol. 38(2), pages 263-283, February.
    2. Egon Balas & Clarence H. Martin, 1980. "Pivot and Complement--A Heuristic for 0-1 Programming," Management Science, INFORMS, vol. 26(1), pages 86-96, January.
    3. Lokketangen, Arne & Glover, Fred, 1998. "Solving zero-one mixed integer programming problems using tabu search," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 624-658, April.
    4. Marianna De Santis & Stefano Lucidi & Francesco Rinaldi, 2010. "Feasibility Pump-Like Heuristics for Mixed Integer Problems," DIS Technical Reports 2010-15, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    5. Egon Balas & Sebastián Ceria & Milind Dawande & Francois Margot & Gábor Pataki, 2001. "Octane: A New Heuristic for Pure 0--1 Programs," Operations Research, INFORMS, vol. 49(2), pages 207-225, April.
    6. S. Lucidi & F. Rinaldi, 2010. "Exact Penalty Functions for Nonlinear Integer Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 145(3), pages 479-488, June.
    7. Walter Murray & Kien-Ming Ng, 2010. "An algorithm for nonlinear optimization problems with binary variables," Computational Optimization and Applications, Springer, vol. 47(2), pages 257-288, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Timo Berthold & Andrea Lodi & Domenico Salvagnin, 2019. "Ten years of feasibility pump, and counting," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 7(1), pages 1-14, March.
    2. M. N. Yarahmadi & S. A. MirHassani & F. Hooshmand, 2023. "A heuristic method to find a quick feasible solution based on the ratio programming," Operational Research, Springer, vol. 23(3), pages 1-19, September.
    3. Guastaroba, G. & Savelsbergh, M. & Speranza, M.G., 2017. "Adaptive Kernel Search: A heuristic for solving Mixed Integer linear Programs," European Journal of Operational Research, Elsevier, vol. 263(3), pages 789-804.
    4. Massimo De Mauri & Joris Gillis & Jan Swevers & Goele Pipeleers, 2020. "A proximal-point outer approximation algorithm," Computational Optimization and Applications, Springer, vol. 77(3), pages 755-777, December.
    5. Marianna De Santis & Sven de Vries & Martin Schmidt & Lukas Winkel, 2022. "A Penalty Branch-and-Bound Method for Mixed Binary Linear Complementarity Problems," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3117-3133, November.
    6. Shaurya Sharma & Brage Knudsen & Bjarne Grimstad, 2016. "Towards an objective feasibility pump for convex MINLPs," Computational Optimization and Applications, Springer, vol. 63(3), pages 737-753, April.
    7. Ma, Cheng & Zhang, Liansheng, 2015. "On an exact penalty function method for nonlinear mixed discrete programming problems and its applications in search engine advertising problems," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 642-656.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marianna De Santis & Stefano Lucidi & Francesco Rinaldi, 2011. "A new class of functions for measuring solution integrality in the Feasibility Pump approach," DIS Technical Reports 2011-08, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    2. Marianna De Santis & Stefano Lucidi & Francesco Rinaldi, 2010. "Feasibility Pump-Like Heuristics for Mixed Integer Problems," DIS Technical Reports 2010-15, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    3. Marianna De Santis & Stefano Lucidi & Francesco Rinaldi, 2010. "New concave penalty functions for improving the Feasibility Pump," DIS Technical Reports 2010-10, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    4. Saïd Hanafi & Raca Todosijević, 2017. "Mathematical programming based heuristics for the 0–1 MIP: a survey," Journal of Heuristics, Springer, vol. 23(4), pages 165-206, August.
    5. Guastaroba, G. & Savelsbergh, M. & Speranza, M.G., 2017. "Adaptive Kernel Search: A heuristic for solving Mixed Integer linear Programs," European Journal of Operational Research, Elsevier, vol. 263(3), pages 789-804.
    6. Ma, Cheng & Zhang, Liansheng, 2015. "On an exact penalty function method for nonlinear mixed discrete programming problems and its applications in search engine advertising problems," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 642-656.
    7. Md Saiful Islam & Md Sarowar Morshed & Md. Noor-E-Alam, 2022. "A Computational Framework for Solving Nonlinear Binary Optimization Problems in Robust Causal Inference," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3023-3041, November.
    8. Freville, Arnaud, 2004. "The multidimensional 0-1 knapsack problem: An overview," European Journal of Operational Research, Elsevier, vol. 155(1), pages 1-21, May.
    9. Raymond R. Hill & Charles H. Reilly, 2000. "The Effects of Coefficient Correlation Structure in Two-Dimensional Knapsack Problems on Solution Procedure Performance," Management Science, INFORMS, vol. 46(2), pages 302-317, February.
    10. M. Santis & F. Rinaldi, 2012. "Continuous Reformulations for Zero–One Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 75-84, April.
    11. Pooyan Kazemian & Yue Dong & Thomas Rohleder & Jonathan Helm & Mark Van Oyen, 2014. "An IP-based healthcare provider shift design approach to minimize patient handoffs," Health Care Management Science, Springer, vol. 17(1), pages 1-14, March.
    12. Weili Zhang & Charles D. Nicholson, 2020. "Objective scaling ensemble approach for integer linear programming," Journal of Heuristics, Springer, vol. 26(1), pages 1-19, February.
    13. Marianna De Santis & Francesco Rinaldi, 2010. "Continuous reformulations for zero-one programming problems," DIS Technical Reports 2010-16, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    14. He, Yan & Wu, Tao & Zhang, Canrong & Liang, Zhe, 2015. "An improved MIP heuristic for the intermodal hub location problem," Omega, Elsevier, vol. 57(PB), pages 203-211.
    15. Hanafi, Said & Freville, Arnaud, 1998. "An efficient tabu search approach for the 0-1 multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 659-675, April.
    16. Altay, Nezih & Robinson Jr., Powell E. & Bretthauer, Kurt M., 2008. "Exact and heuristic solution approaches for the mixed integer setup knapsack problem," European Journal of Operational Research, Elsevier, vol. 190(3), pages 598-609, November.
    17. Filippo Fabiani & Barbara Franci, 2023. "On Distributionally Robust Generalized Nash Games Defined over the Wasserstein Ball," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 298-309, October.
    18. COPPERSMITH, Don & LEE, Jon, 2000. "Indivisibility and divisibility polytopes," LIDAM Discussion Papers CORE 2000031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Javier Cano & Javier M. Moguerza & Francisco J. Prieto, 2017. "Using Improved Directions of Negative Curvature for the Solution of Bound-Constrained Nonconvex Problems," Journal of Optimization Theory and Applications, Springer, vol. 174(2), pages 474-499, August.
    20. Kulturel-Konak, Sadan, 2012. "A linear programming embedded probabilistic tabu search for the unequal-area facility layout problem with flexible bays," European Journal of Operational Research, Elsevier, vol. 223(3), pages 614-625.

    More about this item

    Keywords

    Mixed integer programming; Concave penalty functions; Frank-Wolfe algorithm; Feasibility Problem;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aeg:report:2013-05. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Antonietta Angelica Zucconi (email available below). General contact details of provider: https://edirc.repec.org/data/dirosit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.