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In daily life events, there are many complexities arising from lack of information and uncertainty. Fuzzy linear programming model has been developed to reduce or eliminate this complexity. Fuzzy linear programming is the process of choosing the optimum solution from among the decision alternatives to achieve a specific purpose in cases where the information is not certain. One of the fields where the lack of information or uncertainty makes it difficult to decide is financial markets. Investors who have a certain amount of accumulations are aiming to increase in various ways as well as protecting the value of their income. While doing this, encounter the problem of deciding to which investment vehicle they need to invest in what extent. Therefore, investors apply to fuzzy linear programming model to eliminate this uncertainty and to create the optimal portfolio. In the portfolio selection process suggestions in the literature, the determination of criteria weights is based on triangular fuzzy numbers. In this study, as an alternative to the Enea and Piazza's portfolio selection model, which uses the triangular fuzzy numbers for criteria weighting, a new model that uses the trapezoidal fuzzy numbers for the same aim was proposed. With the solution of the linear programming model which is based on the determined weights, an alternative solution has been produced to the problem of which investment instrument will be invested at what proportion. The results obtained from the existing methods and the results obtained from the proposed model were compared.

Decision making for portfolio selection by fuzzy multi criteria linear programming