The objective coefficient ranging analysis, discussed in the last example, is useful for accessing the effects of changing costs and returns on the optimal solution if each objective function ...

Traditional sensitivity analysis in linear programming usually focuses on variations of one coefficient or term at a time. The tolerance approach was proposed to provide a decision maker with an ...

After an optimal portfolio is identified, sensitivity analysis of the objective function coefficients (the expected returns) might be of interest. This presents a problem however, since sensitivity ...

The quadratic component of the objective function is the covariance of gain between the securities; the first constraint is a proportionality constraint; and the second constraint gives the minimum ...