Optimization is a procedure of finding and comparing feasible solutions until no better solution can be found. It can be divided into several fields, one of which is the Convex Optimization. It is characterized by a convex objective function and convex constraint functions over a convex set which is the set of the decision variables. This can be viewed, on the one hand, as a particular case of ...

This article considers bilevel linear programming problems where the coefficients of the objective functions in the problem are given as a possibilistic variable characterized by a quadratic membership function. An extended Stackelberg solution is defined by incorporating the notions of possibility theory into the original concept of Stackelberg solutions. The characteristic of the proposed mod...

This paper incorporates fuzzy random variables with a portfolio selection problem based on the single index model. The rate of return on each investment can be represented with a fuzzy random variable. A novel decision-making model based both on possibilistic programming and on stochastic programming. It is shown that the formulated problem is transformed into the deterministic equivalent nonli...

Maintaining the health of people during and after a disaster is one of the most important issues in disaster management. Blood products are among the essential items needed to save the human life and the lack of them may lead to significant losses in human health. In this paper a comprehensive mathematical model of blood products supply chain is presented to respond the need for blood products ...

This paper considers multiobjective linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of fractile criteria optimization into a possibilistic programming model. An interactive fuzzy satisficing method is presented for deriving a satisficing solution for a deci...

Fuzzy answer set programming (FASP) is a generalization of answer set programming to continuous domains. As it can not readily take uncertainty into account, however, FASP is not suitable as a basis for approximate reasoning and cannot easily be used to derive conclusions from imprecise information. To cope with this, we propose an extension of FASP based on possibility theory. The resulting fr...

Consider the following (standard) linear programming problem: maximise a real-valued linear function CT x defined for optimisation variables x in Rn that have to satisfy the constraints Ax ≤ B, x ≥ 0, where the matrices A, B, and C are independent random variables that take values a, b, and c in Rm×n, Rm and Rn, respectively. Using an approach we developed in previous work [3], the problem is f...