SUNConferences, Southern African Institute of Industrial Engineering 2013

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A Linear Programming Model For Malt Blending
Tawanda Mutangi, Lungile Nyanga, André van der Merwe, Givemore Kanyemba, T K Chikowore

Last modified: 2013-06-25

Abstract


Quality factors are extremely important in the malting industry. The potential value of blending depends largely on the variability of quality attributes and operations. It stands to reason that higher variability in quality attributes would result in greater blending opportunities and higher net revenues for grain handlers as they can blend malt with lower malt score to produce a blend with a higher malt score. End-users of grain can employ blending to reduce acquisition costs by buying lower quality grain at a discount and blending it with higher quality grain hence will be able to meet malt quality specifications at a lower cost. Blending is widely recognized as a linear programming model but most linear programming models for malt blending have a maximum of five constraints. The paper shows how linear programming can be used to solve a problem which has up to fifteen constraints. In each experiment two samples of low quality malt were mixed to obtain a malt blend with higher quality. The outcome of experiments indicated that the blend had an average malt score deviation of 0.254 from the target which is an improvement from a deviation of 0.919 of the original batch with lower quality.


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