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Non-Submodular Maximization with Matroid and Knapsack Constraints

Author

Listed:
  • Yijing Wang

    (Department of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, P. R. China)

  • Donglei Du

    (Faculty of Management, University of New Brunswick, Fredericton E3B 5A3, Canada)

  • Yanjun Jiang

    (School of Mathematics and Statistics Science, Ludong University, Yantai 264025, P. R. China)

  • Xianzhao Zhang

    (School of Mathematics and Statistics, Linyi University, Linyi 276005, P. R. China)

Abstract

We investigate the problem of maximizing a γ-submodular function subject to one or multiple matroid constraints and one knapsack constraint. By the greedy local search technique, we present approximation algorithms with constant approximation ratios. When γ = 1, our model reduces to the regular submodular maximization problem investigated in the literature under the same type of constraints. Our results therefore contribute towards the line of research on constrained non-submodular function maximization.

Suggested Citation

  • Yijing Wang & Donglei Du & Yanjun Jiang & Xianzhao Zhang, 2021. "Non-Submodular Maximization with Matroid and Knapsack Constraints," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 38(05), pages 1-22, October.
    • Handle: RePEc:wsi:apjorx:v:38:y:2021:i:05:n:s0217595921400017
    DOI: 10.1142/S0217595921400017
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    Cited by:

    1. Majun Shi & Zishen Yang & Wei Wang, 2023. "Greedy Guarantees for Non-submodular Function Maximization Under Independent System Constraint with Applications," Journal of Optimization Theory and Applications, Springer, vol. 196(2), pages 516-543, February.

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