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Among other limitations of O. R the followings deserve mention:
a. Basis: The operational researchers must be unbiased. An attempt to shoehorn result sin to a confirmation of management prior preferences can greatly increase the likelihood of failure.
b. Inadequate Objective Functions: The use of a single objective functions is often an insufficient basis for decisions. Laws regulations public relations market strategies etc. May all serve to overrule a choice arrived at in this way.
c. Internal Resistance: The implementation an optimal decision may also confront internal obstacles such as tribe unions or individual managers with strong preferences for other ways of doing the job.
d. Competence: Competent O. R analysis calls for the careful specifications of alternatives a full comprehension of the underlying mathematical relationship and a huge mass, of data. Formulation of an industrial problem to an O. R set programme is quite often a difficult task.
e. Reliability of the Prepared Solution : At times a non linear relationship is changed to linear for fitting the problem to L. P pattern. This may disturb the solution.
Regression Equations The regression equations express the regression line. As there are two regression lines so there are two regression equations. The regression equatio
Q3. Solve the following Linear Programming Problem using Simple method. Maximize Z= 3x1 + 2X2 Subject to the constraints: X1+ X2 = 4 X1 - X2 = 2 X1, X2 = 0
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What is meant by a mathematical model of a real situation? Discuss the importance of models in the solution of Operations research problems
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