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Solving Linear Integer Models with Variable Bounding

Author

Listed:
  • Elias Munapo

    (Department of Business Statistics and Operations Research, School of Economic Sciences, North West University, Mafikeng Campus, Mmabatho 2745, South Africa)

  • Joshua Chukwuere

    (Department of Information Sciences, School of Economic Sciences, North West University, Mafikeng Campus, Mmabatho 2745, South Africa)

  • Trust Tawanda

    (Department of Statistics and Operations Research, National University of Science and Technology, Ascot, Bulawayo P.O. Box AC 939, Zimbabwe)

Abstract

We present a technique to solve the linear integer model with variable bounding. By using the continuous optimal solution of the linear integer model, the variable bounds for the basic variables are approximated and then used to calculate the optimal integer solution. With the variable bounds of the basic variables known, solving a linear integer model is easier by using either the branch and bound, branch and cut, branch and price, branch cut and price, or branch cut and free algorithms. Thus, the search for large numbers of subproblems, which are unnecessary and common for NP Complete linear integer models, is avoided.

Suggested Citation

  • Elias Munapo & Joshua Chukwuere & Trust Tawanda, 2023. "Solving Linear Integer Models with Variable Bounding," Forecasting, MDPI, vol. 5(2), pages 1-10, May.
    • Handle: RePEc:gam:jforec:v:5:y:2023:i:2:p:24-452:d:1140137
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    References listed on IDEAS

    as
    1. Elias Munapo & Santosh Kumar, 2021. "Reducing the complexity of the knapsack linear integer problem by reformulation techniques," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1087-1093, December.
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