IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v279y2019i1d10.1007_s10479-018-3111-9.html
   My bibliography  Save this article

Approximation schemes for r-weighted Minimization Knapsack problems

Author

Listed:
  • Khaled Elbassioni

    (Masdar Institute, Khalifa University of Science and Technology)

  • Areg Karapetyan

    (Masdar Institute, Khalifa University of Science and Technology)

  • Trung Thanh Nguyen

    (Hai Phong University)

Abstract

Stimulated by salient applications arising from power systems, this paper studies a class of non-linear Knapsack problems with non-separable quadratic constrains, formulated in either binary or integer form. These problems resemble the duals of the corresponding variants of 2-weighted Knapsack problem (a.k.a., complex-demand Knapsack problem) which has been studied in the extant literature under the paradigm of smart grids. Nevertheless, the employed techniques resulting in a polynomial-time approximation scheme (PTAS) for the 2-weighted Knapsack problem are not amenable to its minimization version. We instead propose a greedy geometry-based approach that arrives at a quasi PTAS (QPTAS) for the minimization variant with boolean variables. As for the integer formulation, a linear programming-based method is developed that obtains a PTAS. In view of the curse of dimensionality, fast greedy heuristic algorithms are presented, additionally to QPTAS. Their performance is corroborated extensively by empirical simulations under diverse settings and scenarios.

Suggested Citation

  • Khaled Elbassioni & Areg Karapetyan & Trung Thanh Nguyen, 2019. "Approximation schemes for r-weighted Minimization Knapsack problems," Annals of Operations Research, Springer, vol. 279(1), pages 367-386, August.
    • Handle: RePEc:spr:annopr:v:279:y:2019:i:1:d:10.1007_s10479-018-3111-9
    DOI: 10.1007/s10479-018-3111-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-018-3111-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-018-3111-9?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. Satoru Fujishige & Naoki Katoh & Tetsuo Ichimori, 1988. "The Fair Resource Allocation Problem with Submodular Constraints," Mathematics of Operations Research, INFORMS, vol. 13(1), pages 164-173, February.
    2. Bretthauer, Kurt M. & Shetty, Bala, 2002. "The nonlinear knapsack problem - algorithms and applications," European Journal of Operational Research, Elsevier, vol. 138(3), pages 459-472, May.
    3. Gerhard J. Woeginger, 2000. "When Does a Dynamic Programming Formulation Guarantee the Existence of a Fully Polynomial Time Approximation Scheme (FPTAS)?," INFORMS Journal on Computing, INFORMS, vol. 12(1), pages 57-74, February.
    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. Areg Karapetyan & Khaled Elbassioni & Majid Khonji & Sid Chi-Kin Chau, 2023. "Approximations for generalized unsplittable flow on paths with application to power systems optimization," Annals of Operations Research, Springer, vol. 320(1), pages 173-204, January.

    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. Du-Juan Wang & Yunqiang Yin & Shuenn-Ren Cheng & T.C.E. Cheng & Chin-Chia Wu, 2016. "Due date assignment and scheduling on a single machine with two competing agents," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1152-1169, February.
    2. Janssens, Jochen & Talarico, Luca & Sörensen, Kenneth, 2016. "A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 221-230.
    3. Zhang, Jianzhong & Xu, Chengxian, 2010. "Inverse optimization for linearly constrained convex separable programming problems," European Journal of Operational Research, Elsevier, vol. 200(3), pages 671-679, February.
    4. Yunqiang Yin & Doudou Li & Dujuan Wang & T. C. E. Cheng, 2021. "Single-machine serial-batch delivery scheduling with two competing agents and due date assignment," Annals of Operations Research, Springer, vol. 298(1), pages 497-523, March.
    5. Mohammadivojdan, Roshanak & Geunes, Joseph, 2018. "The newsvendor problem with capacitated suppliers and quantity discounts," European Journal of Operational Research, Elsevier, vol. 271(1), pages 109-119.
    6. Vahideh Sadat Abedi, 2017. "Allocation of advertising budget between multiple channels to support sales in multiple markets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 134-146, February.
    7. AgralI, Semra & Geunes, Joseph, 2009. "Solving knapsack problems with S-curve return functions," European Journal of Operational Research, Elsevier, vol. 193(2), pages 605-615, March.
    8. Lee, Zu-Hsu & Deng, Shiming & Lin, Beixin & Yang, James G.S., 2010. "Decision model and analysis for investment interest expense deduction and allocation," European Journal of Operational Research, Elsevier, vol. 200(1), pages 268-280, January.
    9. R Bai & E K Burke & G Kendall, 2008. "Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1387-1397, October.
    10. Hezhi Luo & Xiaodi Bai & Jiming Peng, 2019. "Enhancing Semidefinite Relaxation for Quadratically Constrained Quadratic Programming via Penalty Methods," Journal of Optimization Theory and Applications, Springer, vol. 180(3), pages 964-992, March.
    11. Feng Li & Zhou Xu & Zhi-Long Chen, 2020. "Production and Transportation Integration for Commit-to-Delivery Mode with General Shipping Costs," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1012-1029, October.
    12. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.
    13. Andjel, Enrique & López, F. Javier & Sanz, Gerardo, 2002. "Ergodicity of one-dimensional resource sharing systems," Stochastic Processes and their Applications, Elsevier, vol. 98(1), pages 1-22, March.
    14. Selçuk, B. & Özlük, Ö., 2013. "Optimal keyword bidding in search-based advertising with target exposure levels," European Journal of Operational Research, Elsevier, vol. 226(1), pages 163-172.
    15. Sathaye, Nakul & Madanat, Samer, 2011. "A bottom-up solution for the multi-facility optimal pavement resurfacing problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1004-1017, August.
    16. Dujuan Wang & Yunqiang Yin & T.C.E. Cheng, 2017. "A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(1), pages 41-63, February.
    17. Sterna, Malgorzata, 2011. "A survey of scheduling problems with late work criteria," Omega, Elsevier, vol. 39(2), pages 120-129, April.
    18. Berlińska, Joanna & Przybylski, Bartłomiej, 2021. "Scheduling for gathering multitype data with local computations," European Journal of Operational Research, Elsevier, vol. 294(2), pages 453-459.
    19. Federico Della Croce & Dominique Quadri, 2012. "Improving an exact approach for solving separable integer quadratic knapsack problems," Journal of Combinatorial Optimization, Springer, vol. 23(1), pages 21-28, January.
    20. Isada, Yuriko & James, Ross J. W. & Nakagawa, Yuji, 2005. "An approach for solving nonlinear multi-objective separable discrete optimization problem with one constraint," European Journal of Operational Research, Elsevier, vol. 162(2), pages 503-513, April.

    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:spr:annopr:v:279:y:2019:i:1:d:10.1007_s10479-018-3111-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.