Nonlinear Functional Analysis and Applications

Kyungnam University, Department of Mathematics Eduaction (경남대학교 수학교육과)
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MONOTONIC OPTIMIZATION TECHNIQUES FOR SOLVING KNAPSACK PROBLEMS

  • Received : 2020.11.23
  • Accepted : 2021.03.20
  • Published : 2021.09.15
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Abstract

In this paper, we propose a new branch-reduction-and-bound algorithm to solve the nonlinear knapsack problems by using general discrete monotonic optimization techniques. The specific properties of the problem are exploited to increase the efficiency of the algorithm. Computational experiments of the algorithm on problems with up to 30 variables and 5 different constraints are reported.

Keywords

Acknowledgement

This work was supported by the Basic Science Research Program through the National Research Foundation(NRF) Grant funded by Ministry of Education of the republic of Korea (2018R1D1A1B07045427).

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