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 440 articles , 3 standard articles )

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  1. Fampa, M.; Lubke, D.; Wang, F.; Wolkowicz, H.: Parametric convex quadratic relaxation of the quadratic knapsack problem (2020)
  2. Anastasiadis, Eleftherios; Deng, Xiaotie; Krysta, Piotr; Li, Minming; Qiao, Han; Zhang, Jinshan: Network pollution games (2019)
  3. Bonami, Pierre; Lodi, Andrea; Schweiger, Jonas; Tramontani, Andrea: Solving quadratic programming by cutting planes (2019)
  4. Coindreau, Marc-Antoine; Gallay, Olivier; Zufferey, Nicolas; Laporte, Gilbert: Integrating workload smoothing and inventory reduction in three intermodal logistics platforms of a European car manufacturer (2019)
  5. Della Croce, Federico; Pferschy, Ulrich; Scatamacchia, Rosario: On approximating the incremental knapsack problem (2019)
  6. Della Croce, Federico; Pferschy, Ulrich; Scatamacchia, Rosario: New exact approaches and approximation results for the penalized knapsack problem (2019)
  7. Dell’Amico, Mauro; Delorme, Maxence; Iori, Manuel; Martello, Silvano: Mathematical models and decomposition methods for the multiple knapsack problem (2019)
  8. Fang, Ethan X.; Liu, Han; Wang, Mengdi: Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach (2019)
  9. Gurski, Frank; Rehs, Carolin; Rethmann, Jochen: Knapsack problems: a parameterized point of view (2019)
  10. Malaguti, Enrico; Monaci, Michele; Paronuzzi, Paolo; Pferschy, Ulrich: Integer optimization with penalized fractional values: the knapsack case (2019)
  11. Ma, Ning; Liu, Ya; Zhou, Zhili: Two heuristics for the capacitated multi-period cutting stock problem with pattern setup cost (2019)
  12. Novak, Antonin; Sucha, Premysl; Hanzalek, Zdenek: Scheduling with uncertain processing times in mixed-criticality systems (2019)
  13. Schulze, Britta; Klamroth, Kathrin; Stiglmayr, Michael: Multi-objective unconstrained combinatorial optimization: a polynomial bound on the number of extreme supported solutions (2019)
  14. Soares Velasco, André; Uchoa, Eduardo: Improved state space relaxation for constrained two-dimensional guillotine cutting problems (2019)
  15. Yang, Zhen; Chen, Haoxun; Chu, Feng; Wang, Nengmin: An effective hybrid approach to the two-stage capacitated facility location problem (2019)
  16. Araujo, Rodolfo Pereira; Rios, Eyder; Coelho, Igor Machado; Marzulo, Leandro A. J.; Clicia Castro, Maria: A novel list-constrained randomized VND approach in GPU for the traveling thief problem (2018)
  17. Bednarczuk, Ewa M.; Miroforidis, Janusz; Pyzel, Przemysław: A multi-criteria approach to approximate solution of multiple-choice knapsack problem (2018)
  18. Ben Salem, Mariem; Taktak, Raouia; Mahjoub, A. Ridha; Ben-Abdallah, Hanêne: Optimization algorithms for the disjunctively constrained knapsack problem (2018)
  19. Carvalho, Desiree M.; Nascimento, Mariá C. V.: A kernel search to the multi-plant capacitated lot sizing problem with setup carry-over (2018)
  20. Czibula, Oliver G.; Gu, Hanyu; Zinder, Yakov: Planning personnel retraining: column generation heuristics (2018)

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