Possibilistic logic in general [7, 8, 9, 10] investigates how possibilistic uncertainty about propositions is propagated when making inferences in a formal logical system. In this paper, we look at a very particular aspect of possibilistic logic: we investigate how, under certain independence assumptions, the introduction of possibilistic uncertainty in classical propositional logic leads to th...

[naeini1] in this paper, a new method is proposed to find the fuzzy optimal solution of fuzzy multi-objective linear programming problems (fmolpp) with fuzzy right hand side and fuzzy decision variables. due to the imprecise nature of available resources, determination of a definitive solution to the model seems impossible. therefore, the proposed model is designed in order to make fuzzy decisi...

In the traditional treatment, risk situations are modeled by random variables. This paper focuses on risk situations described by fuzzy numbers. The goal of the paper is to define and characterize possibilistic risk aversion and study some of its indicators. Key–Words: Possibilistic risk aversion, possibilistic indicators

In this paper, we compare merging operators in possibilistic logic. We first propose an approach to evaluating the discriminating power of a merging operator. After that, we analyze the computational complexity of existing possibilistic merging operators. Finally, we consider the compatibility of possibilistic merging operators with propositional merging operators.

Possibilistic logic provides a convenient tool for dealing with inconsistency and handling uncertainty. In this paper, we propose possibilistic description logics (DLs) as an extension of description logics. We give semantics and syntax of possibilistic description logics. Two kinds of inference services are considered in our logics and algorithms are provided for them. These algorithms are imp...

The aim of this paper is to propose a generalization of previous approaches in qualitative decision making. Our work is based on the binary possibilistic utility (PU), which is a possibilistic counterpart of Expected Utility (EU). We first provide a new axiomatization of PU and study its relation with the lexicographic aggregation of pessimistic and optimistic utilities. Then we explain the rea...

A generalized approach to possibilistic clustering algorithms was proposed in [19], where the memberships are evaluated directly according to the data information using the fuzzy set theory, and the cluster centers are updated via a performance index. The computational experiments based on the generalized possibilistic clustering algorithms in [19] revealed that these clustering algorithms coul...

The goal of this research is to develop a novel second-generation-based biogas supply chain network design (BG-SCND) model that takes into account the triple bottom line approach. Biogas promising renewable energy source can be obtained from variety easily accessible second-generation wastes, including animal manure, municipal waste, and agricultural leftovers. Integrated optimization generatio...

Possibility theory is applied to introduce and reason about the fundamental notion of a key for uncertain data. Uncertainty is modeled qualitatively by assigning to tuples of data a degree of possibility with which they occur in a relation, and assigning to keys a degree of certainty which says to which tuples the key applies. The associated implication problem is characterized axiomatically an...

Nowadays, the design of a strategic supply chain network under disruption is one of the most important priorities of the governments. One of the strategic purposes of managers is to supply the sustainable agricultural products and food in stable conditions which require the production of soil nutrients. In this regard, some disruptions such as sanctions and natural disasters have a destructive ...