Maselle Joseph Kadenge

Work place: Department of Applied Mathematics and Computational Science, Nelson Mandela Institution of Science and Technology, P.O.BOX 447, Arusha, Tanzania.



Research Interests: Computer systems and computational processes, Computational Mathematics


Maselle Joseph Kadenge is a graduate student at Nelson Mandela Institution of Science and Technology, Arusha, Tanzania. Currently, he is pursuing MSc. in Applied Mathematics and Computational Science. His Bachelor degree (BSc.Ed) is in Physics, Mathematics, and Education from the University of Dar es Salaam, awarded in 2006. Moreover, he has Masters of Business Administration in Corporate Management (MBACM) obtained from the Mzumbe University, Tanzania in 2010. His research interest is in Operation research.

Author Articles
Multi-Criteria Decision Making and Numerical Optimization Approaches for Optimizing Water Loss Management Strategies in Water Distribution System - A case of Urban Water Supply and Sanitation Authorities in Tanzania

By Maselle Joseph Kadenge Mashaka Mkandawile Verdiana Grace Masanja

DOI:, Pub. Date: 8 Feb. 2020

Water loss in water distribution systems (WDS) is a serious problem in Tanzania and the third world countries at large. A lot of water is lost on its way before reaching the consumers. This causes a shortage of water supply which leads to loss of revenues of the concerned water authorities. The control or reduction of water loss in the WDS is closely dependent on the commitment of the decision-makers and on the strategies and budget, they set for that purpose. This paper presents a combined model of Multi-Criteria Decision Making (MCDM) and Numerical optimization techniques which may help decision-makers to prioritize and select the best strategies to be used in the management of water loss in the WDS at Moshi Urban Water Supply and Sanitation Authority (MUWSA), Tanzania. The Multi-Criteria Decision Making family methods namely the Multi-Attribute Value Theory (MAVT), Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER), and Complex Proportional Assessment (COPRAS) were used to evaluate and prioritize the strategies, whereas the Integer Linear Programming (ILP) technique a numerical optimization technique was used to select the best strategies or alternatives to be employed in water loss management. The results show that the most preferable alternative is replacement of dilapidated pipes while the least preferable alternative is network zoning. The model selects thirteen out of sixteen alternatives, which cost 97% (TZS 235.71 million) of the total budgets set by the water authority to form a portfolio of the best alternatives for water loss management. Furthermore, the model showed robustness as the selected portfolio of alternatives remained the same even when the weights of the evaluation criteria changed.

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