An intelligent node labelling maximum flow algorithm

Trust Tawanda (), Philimon Nyamugure (), Santosh Kumar () and Elias Munapo ()
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Trust Tawanda: National University of Science and Technology
Philimon Nyamugure: National University of Science and Technology
Santosh Kumar: RMIT University
Elias Munapo: North West University

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 4, No 10, 1276-1284

Abstract: Abstract A network based intelligent node labelling (INL) algorithm for solving the maximal flow problem in directed networks is presented. The INL algorithm is intelligent in that it does not make use of augmenting path methodology to compute the maximal flow value. The principle of the INL algorithm is to design an optimal network by balancing the total inflow value with the total outflow value at all intermediate nodes, thus eliminating the excess or stagnant flow and reduction of underutilized outflow arcs. The INL algorithm makes use of at most two iterations to transform the initial maximal flow network with N-nodes into an optimal network with O(VE) worst- case time complexity. Two numerical illustrations were used to demonstrate how the INL algorithm determines the maximal flow value. Computational experiments were considered on three well studied, small instances in the literature. The proposed INL algorithm was compared to other seven existing algorithms in terms of optimal solution and number of iterations.

Keywords: Maximal flow algorithm; Excess flow; Underutilized arcs; Stagnant flow; Network; Optimal flow network (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-023-01930-3

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