Statistics and Operations Research Publications

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Statistics and Operations Research Publications

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    Validation of the DigComp tool and evaluation of the level of digital literacy skills among Zimbabwean in-service secondary school teachers
    (POTRAZ/RCZ, 2024) Dabengwa, I.M.; Moyo, Sibonile; Gashirai, T.B.; Makaza, D.; Makoni, P.; Pasipamire, N.; Chademana, G.K.; Mufudzi, M.; Mandaza, D.; Mapfumo, S.
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    Application of the Equipment Replacement Dynamic Programming Model in Conveyor Belt Replacement: Case Study of a Gold Mining Company
    (MCSER Publishing, 2015-02) Zvipore, David C.; Nyamugure, P; Maposa, D; Lesaoana, Maseka
    As assets age, they generally deteriorate, resulting in rising operating and maintenance costs and decreasing salvage values. In this paper a comprehensive Dynamic Programming-based optimisation solution methodology is used to solve the equipment replacement optimisation problem on the replacement of conveyor belts at a Gold Mining company in Zimbabwe. Given a mining setup with one and two-year old conveyor belts the ultimate objective is to keep or replace the conveyor belt such that the overall cost of material handling is minimised within a five-year period. The findings reveal that this mining system should replace conveyor belts yearly. It is concluded that, an equipment replacement policy for conveyor belts is a necessity in a mining system so as to achieve an optimal contribution to the economic value that a mining system may accrue within a period of time.
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    Forecasting stock prices on the Zimbabwe Stock Exchange (ZSE) using Arima and Arch/Garch models.Research Academy of Social Sciences.
    (Research Academy of Social Sciences, 2014) Mutendadzamera, S.; Mutasa, Farikayi K.
    The main thrust of this study is to find out whether the stock prices on the ZSE can be predicted using ARIMA and ARCH/GARCH models. The ZSE currently does not have a model that predicts stock price movements. Thus this study attempts to explore econometrics models to predict future stock prices on the Zimbabwe Stock Exchange (ZSE) selected counters. Stock price data is differenced and tested for stationarity using KPSS test and the Augmented Dickey Fuller test. The final models are found to be Econet Wireless, ARIMA(1,1,0), Dairiboard, ARIMA(1,1,0), Delta, ARIMA(1,1,1), SeedCo, ARIMA(1,1,1) and Old Mutual, ARIMA(1,1,0). The GARCH(1,1 model for all the counters forecast better than ARIMA models considering the minimum deviations of the forecasted values from the actual ones. This is because the ARCH/GARCH models incorporate new information and analyses the series based on conditional variances where users can forecast future values with up to date information. Old Mutual had the best ARIMA model with the lowest error where as Dairiboard had the best GARCH model as shown by the minimum Schwarz criterion value of 1.365. We conclude that GARCH(1, 1) model outperforms ARIMA models in modeling stock prices in this study.
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    A Two-Product Inventory Model with a Joint Ordering Policy
    (Hindawi Publishing Corporation, 2013-10-12) Masache, A.
    Inventory is one of themost visible and tangible aspects of doing business.This is the reason whymost problems of a business often end up in inventory. Most inventory studies focus on a single type of product or item such that optimality decisions are arrived at for that single product. In this study, we create a scenario where two types of products are considered in such a way that there exists a joint ordering policy. A continuous review inventory model was developed but ended up with a single period review model for simplicity reasons.We tried to exhaust all main cost elements and fed them into the model in addition to investigating the possible limitations that may constrain the whole decision making process. Six constraints were found and a mathematical programming model was developed. We further went on to prove that the mathematical inventory-programming model developed minimises the total inventory cost in such a scenario.
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    A node merging approach to the transhipment problem
    (Springer Publishers, 2015) Tawanda, Trust
    In this paper, a new approach for solving transhipment model as a transportation model is developed and illustrated. The objective is to expose the transhipment problem to algorithms and methods that are transportation problem (TP) based. The principle of this method consists in merging source nodes with transhipment nodes, through utilization of all possible combination connections, transportation costs are summed up respectively. A numerical example is used to illustrate the approach. The least cost method (LCM) is used to solved the TP resulted from a transformed transhipment problem. Linear programming (LP) models are used as proof of correctness, thus we solve the original transhipment model as an LP problem. This study revealed that solutions from LCM are the same as that of LP formulated from the original transhipment model.