An intelligent node labelling maximum flow algorithm

Tawanda, Trust; Nyamugure, Philimon; Kumar, Santosh; Munapo, Elias

doi:10.1007/s13198-023-01930-3

Cited by 1 publication

(1 citation statement)

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“…The algorithm was evaluated on two case studies thus, Pyigyitagon Township network and 14-Bus electricity network. Tawanda et al [15] presented an exact intelligent node labelling maximum flow algorithm that determines maximum flow in any given WSN in two steps. Tawanda et al [16] proposed a matrix based extreme min-cut max-flow algorithm to calculate maximum flow value without making used of augmenting paths.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Network Reconstruction Algorithm to Compute Maximum Flow for Water Supply Network: A Case Study of the City of Bulawayo, Zimbabwe

Tawanda,

Kumar,

Munapo

et al. 2024

Contemp. Math.

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Determining the maximum flow value in Water Supply Networks (WSN) is a common problem that is being faced by many cities during and after designing of WSN. In this article, the network reconstruction (NR) algorithm is applied to compute the maximum flow value for the city’s WSN based on the actual data. The city of Bulawayo has been selected for the following reasons, availability of research data, the city is facing severe water shedding and several studies have focused only on other issues such as alternative water sources, leakage detection and demand forecasting. The goal of this study is to determine the maximum flow value from the sources to the reservoirs. The results have revealed that the computed maximum flow value is within the estimated range of 110,000 cubic meters to 190,000 cubic meters. Dam sensitivity analysis were considered to determine the sources to give maintenance priority before the rain season. Several recommendations were suggested to improve the water supply situation.

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Section: Literature Reviewmentioning

confidence: 99%