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A New Fully Polynomial Time Approximation Scheme for the Knapsack Problem

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  • Hans Kellerer

    (University of Graz)

  • Ulrich Pferschy

    (University of Graz)

Abstract

A fully polynomial time approximation scheme (FPTAS) is presented for the classical 0-1 knapsack problem. The new approach considerably improves the necessary space requirements. The two best previously known approaches need O(n + 1/ε3) and O(n · 1/ε) space, respectively. Our new approximation scheme requires only O(n + 1/ε2) space while also reducing the running time.

Suggested Citation

  • Hans Kellerer & Ulrich Pferschy, 1999. "A New Fully Polynomial Time Approximation Scheme for the Knapsack Problem," Journal of Combinatorial Optimization, Springer, vol. 3(1), pages 59-71, July.
    • Handle: RePEc:spr:jcomop:v:3:y:1999:i:1:d:10.1023_a:1009813105532
    DOI: 10.1023/A:1009813105532
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    References listed on IDEAS

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    1. Magazine, M. J. & Oguz, Osman, 1981. "A fully polynomial approximation algorithm for the 0-1 knapsack problem," European Journal of Operational Research, Elsevier, vol. 8(3), pages 270-273, November.
    2. Eugene L. Lawler, 1979. "Fast Approximation Algorithms for Knapsack Problems," Mathematics of Operations Research, INFORMS, vol. 4(4), pages 339-356, November.
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    Cited by:

    1. Halman, Nir & Kellerer, Hans & Strusevich, Vitaly A., 2018. "Approximation schemes for non-separable non-linear boolean programming problems under nested knapsack constraints," European Journal of Operational Research, Elsevier, vol. 270(2), pages 435-447.
    2. Rebi Daldal & Iftah Gamzu & Danny Segev & Tonguç Ünlüyurt, 2016. "Approximation algorithms for sequential batch‐testing of series systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(4), pages 275-286, June.
    3. Kellerer, Hans & Kubzin, Mikhail A. & Strusevich, Vitaly A., 2009. "Two simple constant ratio approximation algorithms for minimizing the total weighted completion time on a single machine with a fixed non-availability interval," European Journal of Operational Research, Elsevier, vol. 199(1), pages 111-116, November.
    4. Jooken, Jorik & Leyman, Pieter & De Causmaecker, Patrick, 2022. "A new class of hard problem instances for the 0–1 knapsack problem," European Journal of Operational Research, Elsevier, vol. 301(3), pages 841-854.
    5. Rui Diao & Ya-Feng Liu & Yu-Hong Dai, 2017. "A new fully polynomial time approximation scheme for the interval subset sum problem," Journal of Global Optimization, Springer, vol. 68(4), pages 749-775, August.
    6. Thomas Erlebach & Hans Kellerer & Ulrich Pferschy, 2002. "Approximating Multiobjective Knapsack Problems," Management Science, INFORMS, vol. 48(12), pages 1603-1612, December.
    7. Caprara, Alberto & Kellerer, Hans & Pferschy, Ulrich & Pisinger, David, 2000. "Approximation algorithms for knapsack problems with cardinality constraints," European Journal of Operational Research, Elsevier, vol. 123(2), pages 333-345, June.
    8. Zhenbo Wang & Wenxun Xing, 2009. "A successive approximation algorithm for the multiple knapsack problem," Journal of Combinatorial Optimization, Springer, vol. 17(4), pages 347-366, May.
    9. Francisco Castillo-Zunino & Pinar Keskinocak, 2021. "Bi-criteria multiple knapsack problem with grouped items," Journal of Heuristics, Springer, vol. 27(5), pages 747-789, October.
    10. Zhong, Xueling & Ou, Jinwen & Wang, Guoqing, 2014. "Order acceptance and scheduling with machine availability constraints," European Journal of Operational Research, Elsevier, vol. 232(3), pages 435-441.
    11. Luca Bertazzi, 2012. "Minimum and Worst-Case Performance Ratios of Rollout Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 152(2), pages 378-393, February.
    12. Stephan Helfrich & Arne Herzel & Stefan Ruzika & Clemens Thielen, 2022. "An approximation algorithm for a general class of multi-parametric optimization problems," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1459-1494, October.
    13. Zhou Xu, 2013. "The knapsack problem with a minimum filling constraint," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(1), pages 56-63, February.

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