Department of Mechanical and Production Engineering

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Browsing Department of Mechanical and Production Engineering by Author "Kizito, Paul Mubiru"

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    Investment decision modeling for transboundary project portfolio selection
    (Journal of Management and Science, 2021-09) Kizito, Paul Mubiru; Christopher, Senfuka; Maureen, Ssempijja
    Joint activities for global water partnerships in regional development programs are usually facilitated by implementing transboundary water projects. Most projects are however hampered by the absence of a clear economic base for making investment decisions. In this paper, we propose a zero-one integer programming model to determine the optimal decisions for selection of project portfolios on transboundary waters; where project selection is based on several time periods in the future. The objective is to determine whether to undertake a project or not; so that the net present value of investment returns is maximized to support needy communities. A numerical example is presented for illustration; demonstrating the optimal choice of investment projects under budget constraints. The zero-one integer programming model provides a feasible solution for choice of transboundary project investment decisions; given the competing nature of capital budgets prior project implementation. The proposed model can be efficient; where limited funds among competing projects serve as a basis for project selection criteria; a decision for facilitation enhancement towards water partnership for regional development.
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    Modelling and optimization of residential electricity load under stochastic demand
    (International Journal of Research in Industrial Engineering, 2024-01) Kizito, Paul Mubiru; Ssempijja, Maureen Nalubowa
    The paper considers a modelling framework for a set of households in residential areas using electricity as a form of energy for domestic consumption. Considering the demand and availability of units for electricity consumption, optimal decisions for electricity load allocation are paramount to sustain energy management. We formulate this problem as a stochastic decision-making process model where electricity demand is characterized by Markovian demand. The demand and supply phenomena govern the loading and operational framework, where shortage costs are realized when demand exceeds supply. Empirical data for electricity consumption was collected from fifty households in two residential areas within the suburbs of Kampala in Uganda. Data collection was made at hourly intervals over a period of four months. The major problem focussed on determining an optimal electricity loading decision to minimize consumption costs as demand changes from one state to another. Considering a multi-period planning horizon, an optimal decision was determined for loading or not loading additional electricity units using the Markov decision process approach. The model was tested, and the results demonstrated the existence of optimal state-dependent decision and consumption costs considering the case study used in this study. The proposed model can be cost-effective for managers in the electricity industry. Improved efficiency and utilization of resources for electricity distribution systems to residential areas were realized, with subsequently enhanced service reliability to essential energy market customers.