Baton​ Rouge's Mt. Cedar Hospital is a​ large, private,​ 600-bed facility complete with​ laboratories, operating​ rooms, and​ X-ray equipment. In seeking to increase​ revenues, Mt.​ Cedar's administration has decided to make a​ 90-bed addition on a portion of adjacent land currently used for staff parking. The administrators feel that the​ labs, operating​ rooms, and​ X-ray department are not being fully utilized at present and do not need to be expanded to handle additional patients. The addition of 90 ​beds, however, involves deciding how many beds should be allocated to the medical staff​ (for medical​ patients) and how many to the surgical staff​ (for surgical​ patients).   The​ hospital's accounting and medical records departments have provided the following pertinent information. The average hospital stay for a medical patient is 8 days, and the average medical patient generates $2,280 in revenues. The average surgical patient is in the hospital 5 days and generates $1,515 in revenues. The laboratory is capable of handling 14,500 tests per year more than it was handling. The average medical patient requires 3.1 lab​ tests, the average surgical patient 2.6 lab tests. ​ Furthermore, the average medical patient uses 1 X-ray, the average surgical patient 2 X-rays. If the hospital were expanded by 90 beds, the​ X-ray department could handle up to 7,200 ​X-rays without significant additional cost. ​ Finally, the administration estimates that up to 2,700 additional operations could be performed in existing​ operating-room facilities. Medical​ patients, of​ course, require no​ surgery, whereas each surgical patient generally has one surgery performed.   Develop LP model and using graphical​ solution, determine the optimal solution.

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Baton​ Rouge's Mt. Cedar Hospital is a​ large, private,​ 600-bed facility complete with​ laboratories, operating​ rooms, and​ X-ray equipment. In seeking to increase​ revenues, Mt.​ Cedar's administration has decided to make a​ 90-bed addition on a portion of adjacent land currently used for staff parking. The administrators feel that the​ labs, operating​ rooms, and​ X-ray department are not being fully utilized at present and do not need to be expanded to handle additional patients. The addition of 90 ​beds, however, involves deciding how many beds should be allocated to the medical staff​ (for medical​ patients) and how many to the surgical staff​ (for surgical​ patients).
 
The​ hospital's accounting and medical records departments have provided the following pertinent information. The average hospital stay for a medical patient is 8 days, and the average medical patient generates $2,280
in revenues. The average surgical patient is in the hospital 5 days and generates $1,515 in revenues. The laboratory is capable of handling 14,500 tests per year more than it was handling. The average medical patient requires 3.1 lab​ tests, the average surgical patient 2.6 lab tests. ​ Furthermore, the average medical patient uses
1 X-ray, the average surgical patient 2 X-rays. If the hospital were expanded by 90 beds, the​ X-ray department could handle up to 7,200 ​X-rays without significant additional cost. ​ Finally, the administration estimates that up to
2,700 additional operations could be performed in existing​ operating-room facilities. Medical​ patients, of​ course, require no​ surgery, whereas each surgical patient generally has one surgery performed.
 
Develop LP model and using graphical​ solution, determine the optimal solution.
 
Decision​ variables: X1 ​= number of medical patients
X2 ​= number of surgical patients
 
 
 
 
 
**Decision Variables:**

- \( X_1 \) = number of medical patients
- \( X_2 \) = number of surgical patients

**Aim of the objective function should be**

- [Drop-down option] expected revenue as a result of expansion

**Objective Value \( Z = \)** 
[Input box]

**Subject to:**

- [Drop-down option] (patient days available) - \( C_1 \)
- [Drop-down option] (lab tests) - \( C_2 \)
- [Drop-down option] (X rays) - \( C_3 \)
- [Drop-down option] (surgeries) - \( C_4 \)

\( X_1, X_2 \geq 0 \)

Constraints \( C_1, C_2, C_3, \) and \( C_4 \) using the line graphing tool have been plotted on the graph provided on right.

**Using the point drawing tool,** locate all the corner points for the feasible area on the graph.

**The optimum solution is:**

- \( X_1 = \) [Input box] (round your response to two decimal places).
- \( X_2 = \) [Input box] (round your response to two decimal places).

**Optimal solution value \( Z = \)** [Input box] (round your response to two decimal places).

**% of beds to be assigned to medical patients =** [Input box]% (round your response to one decimal place).

**% of beds to be assigned to surgical patients =** [Input box]% (round your response to one decimal place).

Out of the given 90 beds, medical patients should get [Input box] beds (round your response to the nearest whole number).

Surgical patients should get [Input box] beds (round your response to the nearest whole number).
Transcribed Image Text:**Decision Variables:** - \( X_1 \) = number of medical patients - \( X_2 \) = number of surgical patients **Aim of the objective function should be** - [Drop-down option] expected revenue as a result of expansion **Objective Value \( Z = \)** [Input box] **Subject to:** - [Drop-down option] (patient days available) - \( C_1 \) - [Drop-down option] (lab tests) - \( C_2 \) - [Drop-down option] (X rays) - \( C_3 \) - [Drop-down option] (surgeries) - \( C_4 \) \( X_1, X_2 \geq 0 \) Constraints \( C_1, C_2, C_3, \) and \( C_4 \) using the line graphing tool have been plotted on the graph provided on right. **Using the point drawing tool,** locate all the corner points for the feasible area on the graph. **The optimum solution is:** - \( X_1 = \) [Input box] (round your response to two decimal places). - \( X_2 = \) [Input box] (round your response to two decimal places). **Optimal solution value \( Z = \)** [Input box] (round your response to two decimal places). **% of beds to be assigned to medical patients =** [Input box]% (round your response to one decimal place). **% of beds to be assigned to surgical patients =** [Input box]% (round your response to one decimal place). Out of the given 90 beds, medical patients should get [Input box] beds (round your response to the nearest whole number). Surgical patients should get [Input box] beds (round your response to the nearest whole number).
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