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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ISBN:9781337406659
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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
 
 
 
 
 
variables.
X₁ = number of medical patients
X₂ = number of surgical patients
Aim of the objective function should be
Objective Value Z =
Subject to:
expected revenue as a result of expansion
(patient days available) - C₁
(lab tests) - C₂
(X rays) - C3
(surgeries) - C4
X₁, X₂ ≥0
Constraints, C₁, C₂, C3, and C4 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:
X₁ =
X₂ =
(round your response to two decimal places).
(round your response to two decimal places).
Optimal solution value Z = (round your response to two decimal places).
% of beds to be assigned to medical patients =
% of beds to be assigned to surgical patients =
% (round your response to one decimal place).
% (round your response to one decimal place).
Out of the given 90 beds, medical patients should get beds (round your response to the nearest whole
number).
Surgical patients should get beds (round your response to the nearest whole number).
Transcribed Image Text:variables. X₁ = number of medical patients X₂ = number of surgical patients Aim of the objective function should be Objective Value Z = Subject to: expected revenue as a result of expansion (patient days available) - C₁ (lab tests) - C₂ (X rays) - C3 (surgeries) - C4 X₁, X₂ ≥0 Constraints, C₁, C₂, C3, and C4 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: X₁ = X₂ = (round your response to two decimal places). (round your response to two decimal places). Optimal solution value Z = (round your response to two decimal places). % of beds to be assigned to medical patients = % of beds to be assigned to surgical patients = % (round your response to one decimal place). % (round your response to one decimal place). Out of the given 90 beds, medical patients should get beds (round your response to the nearest whole number). Surgical patients should get beds (round your response to the nearest whole number).
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