Wednesday, November 20, 2019

INTRODUCTION TO QUANTITATIVE MANAGEMENT Lab Report

INTRODUCTION TO QUANTITATIVE MANAGEMENT - Lab Report Example otal profit that can be obtained while satisfying the constraints (in this case maximum benefit of 710) gave 26 for moulding, 14 for trimming and 13 for packaging. However, these values gave a profit of 705 which is less by 5. What this means is that an increase in either of the tree variables will give a gain value that is way above the limit that the company has in stored for the items (710). Therefore, the optimal values that the manufacturing can order and make optimal profit while satisfying the constraints is 26, 14, and 13 for moulding, trimming, and packaging respectively. Besides, the maximum amount of time that each component of moulding can take is represented in the above table. From the solver output, it is apparent that the production time remained. The maximum production time utilised in the manufacture was less from the total allocated time by 2500, 1700, and 300 for moulding, trimming, and packaging respectively. The remaining time could not be accounted for because any change in any of the three variables resulted in higher increase in the total amount of time allocated for each component. Therefore, the entire time was not utilised to obtain maximum production while satisfying the constraints of the equation. The result given by the solver is the optimal selection for each component that gives a maximum profit. One would argue that since the amount of resources available was not fully utilised its sensitivity was not 100%. However, it is apparent that the sensitivity for this selection was (705 / 710) * 100= 99.2%. Though this sensitivity is not perfect, it is relatively high and appropriate. Therefore, the choice of each component given by the solver is sensitive as per the requirement to satisfy the constraints. Selection of parameters that satisfy constraints at 99% is a better option than a percentage lower because such selection should not exceed the available resource. For this reason, these values were the optimal and maximal choice

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