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Advanced, Contemporary Control pp 275–286Cite as

Approximation Algorithms for Constrained Resource Allocation

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1196))

Abstract

In the paper the problem of effective allocation of a single resource in manufacturing or logistic systems is considered. In order to reduce additional costs, the cardinality constraints are imposed that allow one to allocate the resource only to the limited number of operations. This problem is NP-hard. Two approximation algorithms are proposed and their properties are analyzed. In particular, the worst-case performance of these algorithms is studied, and the results of their experimental comparison are presented.

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References

  1. Caprara, A., Kellerer, H., Pferschy, U., Pisinger, D.: Approximation algorithms for knapsack problems with cardinality constraints. Eur. J. Oper. Res. 123, 333–345 (2000)

    Article  MathSciNet  Google Scholar 

  2. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. The MIT Press, Cambridge (2009)

    MATH  Google Scholar 

  3. de Farias Jr., I.R., Nemhauser, G.L.: A polyhedral study of the cardinality constrained knapsack problem. Mathematical Programming Ser. A 96, 439–467 (2003)

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  4. Kellerer, H., Pferschy, U., Pisinger, D.: Knapsack Problems. Springer, Heidelberg (2004)

    Book  Google Scholar 

  5. Martello, S., Toth, P.: Upper bounds and algorithms for hard 0–1 knapsack problems. Oper. Res. 45, 768–778 (1997)

    Article  MathSciNet  Google Scholar 

  6. Mastrolilli, M., Hutter, M.: Hybrid rounding techniques for knapsack problems. Discrete Appl. Math. 154, 640–649 (2006)

    Article  MathSciNet  Google Scholar 

  7. Pieńkosz, K.: Reduction strategies for the cardinality constrained knapsack problem. In: 22nd IEEE International Conference on Methods and Models in Automation and Robotics, pp. 945–948 (2017). https://doi.org/10.1109/MMAR.2017.8046956

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Institute of Control and Computation Engineering, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Krzysztof Pieńkosz

Authors
  1. Krzysztof Pieńkosz
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Correspondence to Krzysztof Pieńkosz .

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Editors and Affiliations

  1. Institute of Automatic Control, Lodz University of Technology, Lodz, Poland

    Andrzej Bartoszewicz

  2. Institute of Automatic Control, Lodz University of Technology, Lodz, Poland

    Jacek Kabziński

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Pieńkosz, K. (2020). Approximation Algorithms for Constrained Resource Allocation. In: Bartoszewicz, A., Kabziński, J., Kacprzyk, J. (eds) Advanced, Contemporary Control. Advances in Intelligent Systems and Computing, vol 1196. Springer, Cham. https://doi.org/10.1007/978-3-030-50936-1_24

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