Knapsack problems are the simplest NP-hard problems in combinatorial optimization, as they maximize an objective function subject to a single resource constraint. Several variants of the classical 0-1 knapsack problem will be considered with respect to relaxations, bounds, reductions and other algorithmic techniques for the exact solution. Computational results are presented to compare the actual performance of the most effective algorithms published.

References in zbMATH (referenced in 407 articles , 3 standard articles )

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  1. Bednarczuk, Ewa M.; Miroforidis, Janusz; Pyzel, Przemysław: A multi-criteria approach to approximate solution of multiple-choice knapsack problem (2018)
  2. Carvalho, Desiree M.; Nascimento, Mariá C. V.: A kernel search to the multi-plant capacitated lot sizing problem with setup carry-over (2018)
  3. D’Ambrosio, Claudia; Furini, Fabio; Monaci, Michele; Traversi, Emiliano: On the product knapsack problem (2018)
  4. Diaz, Juan Esteban; Handl, Julia; Xu, Dong-Ling: Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system (2018)
  5. Fischetti, Matteo; Monaci, Michele; Sinnl, Markus: A dynamic reformulation heuristic for generalized interdiction problems (2018)
  6. Furini, Fabio; Monaci, Michele; Traversi, Emiliano: Exact approaches for the knapsack problem with setups (2018)
  7. Gadegaard, Sune Lauth; Klose, Andreas; Nielsen, Lars Relund: An improved cut-and-solve algorithm for the single-source capacitated facility location problem (2018)
  8. Kung, Ling-Chieh; Liao, Wei-Hung: An approximation algorithm for a competitive facility location problem with network effects (2018)
  9. Ma, Ning; Liu, Ya; Zhou, Zhili; Chu, Chengbin: Combined cutting stock and lot-sizing problem with pattern setup (2018)
  10. Nassief, W.; Contreras, I.; Jaumard, B.: A comparison of formulations and relaxations for cross-dock door assignment problems (2018)
  11. Zhen, Lu; Wang, Kai; Wang, Shuaian; Qu, Xiaobo: Tug scheduling for hinterland barge transport: a branch-and-price approach (2018)
  12. Álvarez-Miranda, Eduardo; Sinnl, Markus: A relax-and-cut framework for large-scale maximum weight connected subgraph problems (2017)
  13. Avci, Mustafa; Topaloglu, Seyda: A multi-start iterated local search algorithm for the generalized quadratic multiple knapsack problem (2017)
  14. Chen, Yuning; Hao, Jin-Kao: An iterated “hyperplane exploration” approach for the quadratic knapsack problem (2017)
  15. Christensen, Henrik I.; Khan, Arindam; Pokutta, Sebastian; Tetali, Prasad: Approximation and online algorithms for multidimensional bin packing: a survey (2017)
  16. Della Croce, Federico; Salassa, Fabio; Scatamacchia, Rosario: A new exact approach for the 0-1 collapsing knapsack problem (2017)
  17. Della Croce, Federico; Salassa, Fabio; Scatamacchia, Rosario: An exact approach for the 0-1 knapsack problem with setups (2017)
  18. Edirisinghe, Chanaka; Jeong, Jaehwan: Tight bounds on indefinite separable singly-constrained quadratic programs in linear-time (2017)
  19. Enderer, Furkan; Contardo, Claudio; Contreras, Ivan: Integrating dock-door assignment and vehicle routing with cross-docking (2017)
  20. Fischetti, Matteo; Liberti, Leo; Salvagnin, Domenico; Walsh, Toby: Orbital shrinking: theory and applications (2017)

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