The paper focuses on computational aspects of portfolio optimization (PO) problems. The objectives of such problems may include: expectedreturn, standard deviation and variation coefficient of the portfolioreturn rate. PO problems can be formulated as mathematical programming problems in crisp, stochastic or fuzzy environments. To compute optimal solutions of such single- and multi-objective programming problems, the paper proposes the use of a computational optimization method such as RST2ANU method, which can be applied for nonconvex programming problems. Especially, an updated version of the interactive fuzzy utility method, named UIFUM, is proposed to deal with portfolio multi-objective optimization problems.
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The paper focuses on computational aspects of portfolio optimization (PO) problems. The objectives of such problems may include: expectedreturn, standard deviation and variation coefficient of the portfolioreturn rate. PO problems can be formulated as mathematical programming problems in crisp, stochastic or fuzzy environments. To compute optimal solutions of such single- and multi-objective programming problems, the paper proposes the use of a computational optimization method such as RST2ANU method, which can be applied for nonconvex programming problems. Especially, an updated version of the interactive fuzzy utility method, named UIFUM, is proposed to deal with portfolio multi-objective optimization problems.
