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The Linear Programming Problem Whose Output Follows Is Used to Determine

question 44

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The linear programming problem whose output follows is used to determine how many bottles of red nail polish (x1), blue nail polish (x2), green nail polish (x3), and pink nail polish (x4) a beauty salon should stock. The objective function measures profit; it is assumed that every piece stocked will be sold. Constraint 1 measures display space in units, constraint 2 measures time to set up the display in minutes. Note that green nail polish does not require any time to prepare its display. Constraints 3 and 4 are marketing restrictions. Constraint 3 indicates that the maximum demand for red and green polish is 25 bottles, while constraint 4 specifies that the minimum demand for blue, green, and pink nail polish bottles combined is at least 50 bottles.
MAX 100x1+120x2+150x3+125x4100 x _ { 1 } + 120 x _ { 2 } + 150 x _ { 3 } + 125 x _ { 4 }
Subject to 1 . x1+2x2+2x3+2x4108x _ { 1 } + 2 x _ { 2 } + 2 x _ { 3 } + 2 x _ { 4 } \leq 108
   2. 3x1+5x2+x41203 x _ { 1 } + 5 x _ { 2 } + x _ { 4 } \leq 120
   3. x1+x325x _ { 1 } + x _ { 3 } \leq 25
   4. x2+x3+x450x _ { 2 } + x _ { 3 } + x _ { 4 } \geq 50
    x1,x2,x3,x40x _ { 1 } , x _ { 2 } , x _ { 3 } , x _ { 4 } \geq 0
Optimal Solution:
Objective Function Value = 7475.000

 Variable  Value  Reduced  Costs x180x205x3170x4330\begin{array} { c | c | c } \text { Variable } & \text { Value } & \begin{array} { c } \text { Reduced } \\\text { Costs }\end{array} \\\hline x _ { 1 } & 8 & 0 \\x _ { 2 } & 0 & 5 \\x _ { 3 } & 17 & 0 \\x _ { 4 } & 33 & 0\end{array}

 Constraint  Slack/  Surplus  Dual Prices 1075263030254025\begin{array} { c c c } \text { Constraint } & \begin{array} { c } \text { Slack/ } \\\text { Surplus }\end{array} & \text { Dual Prices } \\\hline 1 & 0 & 75 \\2 & 63 & 0 \\3 & 0 & 25 \\4 & 0 & - 25 \\\hline\end{array} Objective Coefficient Ranges

 Variable  Lower  Limit  Current  Value  Upper  Limit x187.5100 none x2 none 120125x3125150162x4120125150\begin{array}{c|c|c|c}\text { Variable } & \begin{array}{c}\text { Lower } \\\text { Limit }\end{array} & \begin{array}{c}\text { Current } \\\text { Value }\end{array} & \begin{array}{c}\text { Upper } \\\text { Limit }\end{array} \\\hline x_{1} & 87.5 & 100 & \text { none } \\x_{2} & \text { none } & 120 & 125 \\x_{3} & 125 & 150 & 162 \\x_{4} & 120 & 125 & 150\end{array} Right Hand Side Ranges

 Constraint  Lower  Limit  Current  Value  Upper  Limit 1100108123.75257120 none 382558441.55054\begin{array} { c c c c } \text { Constraint } & \begin{array} { c } \text { Lower } \\\text { Limit }\end{array} & \begin{array} { c } \text { Current } \\\text { Value }\end{array} & \begin{array} { c } \text { Upper } \\\text { Limit }\end{array} \\\hline 1 & 100 & 108 & 123.75 \\2 & 57 & 120 & \text { none } \\3 & 8 & 25 & 58 \\4 & 41.5 & 50 & 54 \\\hline\end{array}
-a) By how much can the amount of space decrease before there is a change in the profit?
b) By how much can the amount of space decrease before there is a change in the product mix?
c) By how much can the amount of time available to set up the display can increase before the solution (product mix) would change?
d) What is the lowest value for the amount of time available to set up the display increase before the solution (product mix) would change?


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In phylogenetics, a high-level taxonomic rank above the rank of kingdom, used to organize the diversity of eukaryotes especially.

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A group of protists, including dinoflagellates, apicomplexans, and ciliates, characterized by the presence of alveoli (small sac-like structures) beneath their cell membranes.

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