Question #287023

{F} The furniture company inexpensive tables and chairs. The production process of each is similar in the painting department each table take 4 hours of carpentry and 2 hours in the painting department. Each chair requires 3 hours of carpentry and 1 hour painting department. During the current product period 240 hours of carpentry time are available and 100 hrs in the painting is available. Each table sold yields of profit of $7 and chair produced sold for $5 profit. Find the best combination of table and chairs to manufacture in order to reach the maximum number of profit?


1
Expert's answer
2022-02-01T07:46:23-0500

Let x1x_1 = number of tables

x2x_2 = number of chairs

zz = profit

Maximize z=7x1+5x2z=7x_1+5x_2

Subject to constraints:


4x1+3x22404x_1+3x_2\le240 ( Carpentry constraints)


2x1+x21002x_1+x_2\le100 (Painting constraints)


x1,x2x_1,x_2 0\ge0 ( Non-negativity constraints)


Initial system of equations


7x15x2+z=04x1+3x2+s1=2402x1+x2+s2=100-7x_1-5x_2+z=0\\4x_1+3x_2+s_1=240\\2x_1+x_2+s_2=100


Where s1s_1 and s2s_2 are slack variables


x1x2s1s2z4310024021010100750010\begin{matrix} x_1& x_2&s_1&s_2&z&& \\ 4&3&1&0&0&240\\2&1&0&1&0&100\\-7&-5&0&0&1&0 \end{matrix}


Pivot column is 1st1^{st}

Test ratio:

2404=60\frac{240}{4}=60 1002=50\frac{100}{2}=50


Pivot row is 2nd2^{nd}


Using Gaussian Elimination

R2÷2R2R_2÷2\to R_2\> 4R2+R1R1-4R_2+R_1\to R_1

7R2+R3R37R_2+R_3\to R_3


x1x2s1s2z011204010.500.505001.503.51350\begin{matrix} x_1&x_2&s_1&s_2&z&&\\ 0&1&1&-2&0&40\\1&0.5&0&0.5&0&50\\0&-1.5&0&3.5&1&350 \end{matrix}


Pivot column is 2nd2^ {nd}

Test ratio:

401=40\frac{40}{1}=40 500.5=100\frac {50}{0.5}=100


Pivot row is 1st1^{st}



Using Gaussian elimination

½R1+R2R21.5R1+R3R3-½R_1+R_2\to R_2\\1.5R_1+R_3\to R_3


x1x2s1s2z0112040100.50.5030001.50.51410\begin{matrix} x_1&x_2&s_1&s_2&z&&\\0&1&1&-2&0&40\\1&0&-0.5&0.5&0&30\\0&0&1.5&0.5&1&410 \end{matrix}


x1=\therefore x_1= Number of tables =40=40


x2=x_2= Number of chairs=30=30


z=z= Profit=$410= \$ 410


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