Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at object-language level. Solving a P-DeLP query Q accounts for performing an exhaustive analysis of arguments and defeaters for Q, resulting in a so-calle...

This paper discusses a class of uncertain optimization problems, in which unknown parameters are modeled by fuzzy intervals. The membership functions the intervals interpreted as possibility distributions for values parameters. It is shown how known concepts robustness and light robustness, traditional interval uncertainty representation parameters, can be generalized to choose solutions that o...

Mathematical programming plays a pivotal role in finding the solution for optimization problems in various practical, real-life applications. Conventionally, the modeling used in mathematical programming is based on numerical values. It is however complicated to accurately provide such rigid numerical values because uncertain elements do exist in the decision-making process. Furthermore, buildi...

Stability and sensitivity analysis becomes more and more attractive also in the area of multiple objective mathematical programming (for excellent surveys see e.g. [Gal86] and [Rios90]). Publications on this topic usually investigate the impact of parameter changes (in the righthand side or/and the objective function or/and the ’A-matrix’ or/and the domination structure) on the solution in vari...

Possibilistic Stable model Semantics is an extension of Stable Model Semantics that allows to merge uncertain and non monotonic reasoning into a unique framework. To achieve this aim, knowledge is represented by a normal logic program where each rule is given with its own degree of certainty. By this way, it formally defines a distribution of possibility over atom sets that, on its turn, induce...

in this paper, the portfolio selection problem is considered, where fuzziness and randomness appear simultaneously in optimization process. since return and dividend play an important role in such problems, a new model is developed in a mixed environment by incorporating fuzzy random variable as multi-objective nonlinear model. then a novel interactive approach is proposed to determine the pref...

In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network environmental competencies is important problem. This paper presents a new bi-objective mixed integer ma...