Unfortunately, the SCMLP is not a convex programming problem.
The purpose of the algorithm is to simultaneously determine the optimal objective function coefficients and decision variables that solve the SCMLP. The process begins by determining an initial feasible vector of coefficients [c.sub.i].
In the next section, the SCMLP model is demonstrated in the portfolio selection process.
A DEMONSTRATION OF THE PORTFOLIO SELECTION PROCESS USING THE SCMLP MODEL
In that discussion it was claimed that the SCMLP model could best achieve the desired objectives of the Smith model and applications of linear programming procedures to the portfolio selection process without the necessity of having the individual investor place absolute weights on his investment preferences.
The simplex method is used to solve the SCMLP problem.
This research suggests that the SCMLP model is superior to other approaches to the portfolio selection process when the individual preferences of investors extend beyond the simple risk to total return tradeoff.
The SCMLP model, which is explained in this research in a portfolio selection environment, certainly overcomes the problems associated with individual preferences, is not costly to implement, and is not as complex and difficult to explain (as the Markowitz Quadratic Approach).