IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v282y2020i2p453-463.html
   My bibliography  Save this article

An exact algebraic ϵ-constraint method for bi-objective linear integer programming based on test sets

Author

Listed:
  • Hartillo-Hermoso, María Isabel
  • Jiménez-Tafur, Haydee
  • Ucha-Enríquez, José María

Abstract

A new exact algorithm for bi-objective linear integer problems is presented, based on the classic ϵ-constraint method and algebraic test sets for single-objective linear integer problems. Our method provides the complete Pareto frontier N of non-dominated points and, for this purpose, it considers exactly |N| single-objective problems by using reduction with test sets instead of solving with an optimizer. Although we use Gröbner bases for the computation of test sets, which may provoke a bottleneck in principle, the computational results are shown to be promising, especially for unbounded knapsack problems, for which any usual branch-and-cut strategy could be much more expensive. Nevertheless, this algorithm can be considered as a potentially faster alternative to IP-based methods when test sets are available.

Suggested Citation

  • Hartillo-Hermoso, María Isabel & Jiménez-Tafur, Haydee & Ucha-Enríquez, José María, 2020. "An exact algebraic ϵ-constraint method for bi-objective linear integer programming based on test sets," European Journal of Operational Research, Elsevier, vol. 282(2), pages 453-463.
    • Handle: RePEc:eee:ejores:v:282:y:2020:i:2:p:453-463
    DOI: 10.1016/j.ejor.2019.09.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221719307891
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2019.09.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rekha R. Thomas, 1995. "A Geometric Buchberger Algorithm for Integer Programming," Mathematics of Operations Research, INFORMS, vol. 20(4), pages 864-884, November.
    2. Laumanns, Marco & Thiele, Lothar & Zitzler, Eckart, 2006. "An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method," European Journal of Operational Research, Elsevier, vol. 169(3), pages 932-942, March.
    3. Rong, Aiying & Figueira, José Rui, 2014. "Dynamic programming algorithms for the bi-objective integer knapsack problem," European Journal of Operational Research, Elsevier, vol. 236(1), pages 85-99.
    4. Zhang, Weihua & Reimann, Marc, 2014. "A simple augmented ∊-constraint method for multi-objective mathematical integer programming problems," European Journal of Operational Research, Elsevier, vol. 234(1), pages 15-24.
    5. M. Ehrgott & S. Ruzika, 2008. "Improved ε-Constraint Method for Multiobjective Programming," Journal of Optimization Theory and Applications, Springer, vol. 138(3), pages 375-396, September.
    6. Rong, Aiying & Figueira, José Rui, 2013. "A reduction dynamic programming algorithm for the bi-objective integer knapsack problem," European Journal of Operational Research, Elsevier, vol. 231(2), pages 299-313.
    7. Ted Ralphs & Matthew Saltzman & Margaret Wiecek, 2006. "An improved algorithm for solving biobjective integer programs," Annals of Operations Research, Springer, vol. 147(1), pages 43-70, October.
    8. Kirlik, Gokhan & Sayın, Serpil, 2014. "A new algorithm for generating all nondominated solutions of multiobjective discrete optimization problems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 479-488.
    9. Dimitris Bertsimas & Georgia Perakis & Sridhar Tayur, 2000. "A New Algebraic Geometry Algorithm for Integer Programming," Management Science, INFORMS, vol. 46(7), pages 999-1008, July.
    Full references (including those not matched with items on IDEAS)

    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. David Bergman & Merve Bodur & Carlos Cardonha & Andre A. Cire, 2022. "Network Models for Multiobjective Discrete Optimization," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 990-1005, March.
    2. Holzmann, Tim & Smith, J.C., 2018. "Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations," European Journal of Operational Research, Elsevier, vol. 271(2), pages 436-449.
    3. Mesquita-Cunha, Mariana & Figueira, José Rui & Barbosa-Póvoa, Ana Paula, 2023. "New ϵ−constraint methods for multi-objective integer linear programming: A Pareto front representation approach," European Journal of Operational Research, Elsevier, vol. 306(1), pages 286-307.
    4. Schmidt, Adam & Albert, Laura A. & Zheng, Kaiyue, 2021. "Risk management for cyber-infrastructure protection: A bi-objective integer programming approach," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    5. Mohammad S. Roni & Sandra D. Eksioglu & Kara G. Cafferty & Jacob J. Jacobson, 2017. "A multi-objective, hub-and-spoke model to design and manage biofuel supply chains," Annals of Operations Research, Springer, vol. 249(1), pages 351-380, February.
    6. Natashia Boland & Hadi Charkhgard & Martin Savelsbergh, 2015. "A Criterion Space Search Algorithm for Biobjective Integer Programming: The Balanced Box Method," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 735-754, November.
    7. Rong, Aiying & Figueira, José Rui, 2014. "Dynamic programming algorithms for the bi-objective integer knapsack problem," European Journal of Operational Research, Elsevier, vol. 236(1), pages 85-99.
    8. Bashir Bashir & Özlem Karsu, 2022. "Solution approaches for equitable multiobjective integer programming problems," Annals of Operations Research, Springer, vol. 311(2), pages 967-995, April.
    9. Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
    10. Kerstin Dächert & Kathrin Klamroth, 2015. "A linear bound on the number of scalarizations needed to solve discrete tricriteria optimization problems," Journal of Global Optimization, Springer, vol. 61(4), pages 643-676, April.
    11. Dächert, Kerstin & Klamroth, Kathrin & Lacour, Renaud & Vanderpooten, Daniel, 2017. "Efficient computation of the search region in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 260(3), pages 841-855.
    12. Satya Tamby & Daniel Vanderpooten, 2021. "Enumeration of the Nondominated Set of Multiobjective Discrete Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 72-85, January.
    13. Tobias Kuhn & Stefan Ruzika, 2017. "A coverage-based Box-Algorithm to compute a representation for optimization problems with three objective functions," Journal of Global Optimization, Springer, vol. 67(3), pages 581-600, March.
    14. Di Martinelly, Christine & Meskens, Nadine, 2017. "A bi-objective integrated approach to building surgical teams and nurse schedule rosters to maximise surgical team affinities and minimise nurses' idle time," International Journal of Production Economics, Elsevier, vol. 191(C), pages 323-334.
    15. Nathan Adelgren & Akshay Gupte, 2022. "Branch-and-Bound for Biobjective Mixed-Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 909-933, March.
    16. Angelo Aliano Filho & Antonio Carlos Moretti & Margarida Vaz Pato & Washington Alves Oliveira, 2021. "An exact scalarization method with multiple reference points for bi-objective integer linear optimization problems," Annals of Operations Research, Springer, vol. 296(1), pages 35-69, January.
    17. William Pettersson & Melih Ozlen, 2020. "Multiobjective Integer Programming: Synergistic Parallel Approaches," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 461-472, April.
    18. Tolga Bektaş, 2018. "Disjunctive Programming for Multiobjective Discrete Optimisation," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 625-633, November.
    19. Kadziński, Miłosz & Tervonen, Tommi & Tomczyk, Michał K. & Dekker, Rommert, 2017. "Evaluation of multi-objective optimization approaches for solving green supply chain design problems," Omega, Elsevier, vol. 68(C), pages 168-184.
    20. Mavrotas, George & Florios, Kostas & Figueira, José Rui, 2015. "An improved version of a core based algorithm for the multi-objective multi-dimensional knapsack problem: A computational study and comparison with meta-heuristics," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 25-43.

    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:eee:ejores:v:282:y:2020:i:2:p:453-463. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.