Abstract
The knapsack problem arises in a variety of real world applications, including flexible manufacturing systems, railway stations, hydrological studies and others. In this paper, we propose a descent method-based heuristic for tackling a special knapsack problem: the binary quadratic knapsack with conflict graphs. The proposed method combines (i) an intensification search with a descent method for enhancing the accuracy of the solutions and (ii) a diversification strategy which is used for enlarging the search space. The method uses degrading and re-optimization strategies in order to reach a series of diversified solutions. The performance of the proposed method is evaluated on benchmark instances taken from the literature, where its achieved results are compared to those reached by both GLPK solver and the best method available in the literature. The method seems very competitive, where it is able to achieve 37 new lower bounds.


Similar content being viewed by others
References
Billionnet, A., & Soutif, E. (2004). An exact method based on Lagrangian decomposition for the 0–1 quadratic knapsack problem. European Journal of Operational Research, 157, 565–575.
Dantzig, G. B. (1957). Discrete-variable extremum problem. Operations Research, 5(2), 266–288.
GLPK. (2017). GNU linear programming kit. https://www.gnu.org/software/glpk/; https://github.com/PetterS/glpk.
Hifi, M. (2014). An iterative rounding search-based algorithm for the disjunctively constrained knapsack problem. Engineering Optimization, 46(8), 1109–1122.
Hifi, M., & Michrafy, M. (2006). A reactive local search-based algorithm for the disjunctively constrained knapsack problem. Journal of the Operational Research Society, 57, 718–726.
Hifi, M., & Michrafy, M. (2007). Reduction strategies and exact algorithms for the disjunctively knapsack problem. Computers and Operations Research, 34(9), 2657–2673.
Hifi, M., Sadfi, S., & Sbihi, A. (2002). An efficient algorithm for the knapsack sharing problem. Computational Optimization and Applications, 23, 27–45.
Hifi, M., Saleh, S., & Wu, L. (2015). A hybrid guided neighborhood search for the disjunctively constrained knapsack problem. Cogent Engineering,. https://doi.org/10.1080/23311916.2015.1068969.
Hif, M., & Wu, L. (2015). Lagrangian heuristic-based neighborhood search for the multiple-choice multi-dimensional knapsack problem. Engineering Optimization, 47(12), 1619–1636.
Kellerer, H., Pferschy, U., & Pisinger, D. (2004). Knapsack problems. Berlin: Springer.
Martello, S., Pisinger, D., & Toth, P. (1999). Dynamic programming and strong bounds for the 0?1 knapsack problem. Management Science, 45, 414–424.
Merkle, M., & Hellman, M. (1978). Hiding information and signatures in trapdoor knapsacks. IEEE Transactions on Information Theory, 24(5), 525–530.
Perboli, G., Gobbato, L., & Perfetti, F. (2014). Packing problems in transportation and supply chain: New problems and trends. Procedia - Social and Behavioral Sciences, 111, 672–681.
Pferschy, U., & Schauer, J. (2009). The knapsack problem with conflict graphs. Journal of Graph Algorithms and Applications, 13, 233–249.
Shi, X., Wu, L., & Meng, X. (2017). A new optimization model for the sustainable development: Quadratic knapsack problem with conflict graphs. Sustainability, 9(2), 1–10.
Yamada, T., Kataoka, S., & Watanabe, K. (2002). Heuristic and exact algorithms for the disjunctively constrained knapsack problem. Information Processing Society of Japan Journal, 43(9), 2864–2870.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Dahmani, I., Hifi, M. A modified descent method-based heuristic for binary quadratic knapsack problems with conflict graphs. Ann Oper Res 298, 125–147 (2021). https://doi.org/10.1007/s10479-019-03290-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-019-03290-3