Fuzzy Random Linear Optimization under Possibilistic Downside Risk Measures: Minimization of Possibilistic Low Partial Moment
نویسنده
چکیده
This paper considers new downside risk-aversion models for linear optimization (linear programming) with discrete fuzzy random variables. Through new downside risk measures for fuzzy stochastic optimization problems, possibilistic low partial moment (PLPM) models are constructed by incorporating possibility and necessity measures into classical low partial moment. To provide practical models, the case of linear membership functions is focused on. It is shown that the problems involving both fuzziness and randomness are transformed into deterministic polynomial optimization problems.
منابع مشابه
Modeling Decision Making under Uncertainty and Vagueness
This paper discuss mainly issues related for modeling decision making under uncertain, vagueness, risky and imprecise information. There will be presented a description of five ordinal methods for modeling decision making under uncertainty in the context of linguistic data: Possibilistic Decisisonmaking, Revised Possibilistic Decisisonmaking, Commensurate L-Fuzzy Risk Minimization, Fuzzy relati...
متن کاملAn Interactive Possibilistic Programming Approach to Designing a 3PL Supply Chain Network Under Uncertainty
The design of closed-loop supply chain networks has attracted increasing attention in recent decades with environmental concerns and commercial factors. Due to the rapid growth of knowledge and technology, the complexity of the supply chain operations is increasing daily and organizations are faced with numerous challenges and risks in their management. Most organizations with limited resources...
متن کاملDeveloping a multi objective possibilistic programming model for portfolio selection problem
Portfolio selection problem is one of the most important issues in the area of financial management in which is attempted to allocate wealth to different assets with controlling the return and risk. The aim of this paper is to obtain the optimum portfolio with regard to the cardinality and threshold constraints. In the paper, a novel multi-objective possibilistic programming model is developed ...
متن کاملA Possibilistic Mean VaR Model for Portfolio Selection
Abstract: This paper deals with a portfolio selection problem with fuzzy return rates. A possibilistic mean VaR model was proposed for portfolio selection. Specially, we present a mathematical programming model with possibilistic constraint. The possibilistic programming problem can be solved by transforming it into a linear programming problem. A numerical example is given to illustrate the be...
متن کاملFuzzy portfolio optimization model under real constraints
This paper discusses a multi-objective portfolio optimization problem for practical portfolio selection in fuzzy environment, in which the return rates and the turnover rates are characterized by fuzzy variables. Based on the possibility theory, fuzzy return and liquidity are quantified by possibilistic mean, and market risk and liquidity risk are measured by lower possibilistic semivariance. T...
متن کامل