Possibilistic answer set programming (PASP) unites answer set programming (ASP) and possibilistic logic (PL) by associating certainty values with rules. The resulting framework allows to combine both non-monotonic reasoning and reasoning under uncertainty in a single framework. While PASP has been well-studied for possibilistic definite and possibilistic normal programs, we argue that the curre...

Probability assessments of events are often linguistic in nature. We model them by means of possibilistic probabilities (a version of Zadeh’s fuzzy probabilities with a behavioural interpretation) with a suitable shape for practical implementation (on a computer). Employing the tools of interval analysis and the theory of imprecise probabilities we argue that the verification of coherence for t...

This study develops an interactive possibilistic linear programming (PLP) method for solving the integrated production/transportation planning decision (PTPD) problem with imprecise objective and constraints in an uncertain environment. The proposed PLP method attempts to minimize the total net costs with reference to available supply, machine capacity, labor level and budget constraints at eac...

The modeling of complex risk situations imposes the existence of multiple ways to represent the risk and compare the risk situations between them. In probabilistic models, risk is described by random variables and risk situations are compared by stochastic dominance. In possibilistic or credibilistic models, risk is represented by fuzzy variables. This paper concerns three indicators of dominan...

In this paper, both the uncertainty and the origin of pieces of information is handled in an extended possibilistic logic framework. Each formula is associated with a set (a fuzzy set more generally) which gathers labels of sources according to which the formula is (more or less) certainly true. In case of a single source of information, possibilistic logic is recovered. Soundness and completen...

In this paper we consider the extensions of description logics that were proposed to represent uncertain or vague knowledge, focusing on the fuzzy and possibilistic formalisms. We compare these two approaches and comment on their differences concentrating on the consistency issue of knowledge bases represented in these extended frameworks. We present a classification of existing algorithms and ...

Recent research has identified the notion of indirect consistency as a rationality postulate that every rule-based argumentation frameworks should satisfy. Possibilistic Defeasible Logic Programming (PDeLP) is an argumentation framework based on logic programming which incorporates a treatment of possibilistic uncertainty at objectlanguage level, in which indirect consistency does not hold. In ...

Article history: Received 1 January 2010 Received in revised form 5 May 2010 Accepted 18 May 2010 Available online 18 May 2010 In this paper, we present a multi-objective possibilistic programming model to locate distribution centers (DCs) and allocate customers' demands in a supply chain network design (SCND) problem. The SCND problem deals with determining locations of facilities (DCs and/or ...