Extreme Min – Cut Max – Flow Algorithm

Trust Tawanda, Philimon Nyamugure, Elias Munapo and Santosh Kumar
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Trust Tawanda: National University of Science and Technology, Zimbabwe
Philimon Nyamugure: National University of Science and Technology, Zimbabwe
Elias Munapo: North West University, South Africa
Santosh Kumar: RMIT University, Australia

International Journal of Applied Metaheuristic Computing (IJAMC), 2023, vol. 14, issue 1, 1-16

Abstract: In this article, the authors propose a maximum flow algorithm based on flow matrix. The algorithm only requires the effort to reduce the capacity of the underutilized arcs to that of the respective flow. The optimality of the algorithm is proved by the max-flow min-cut theorem. The algorithm is table-based, thus avoiding augmenting path and residual network concepts. The authors used numerical examples and computational comparisons to demonstrate the efficiency of the algorithm. These examples and comparisons revealed that the proposed algorithm is capable of computing exact solutions while using few iterations as compared to some existing algorithms.

Date: 2023
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