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...

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...

From the past, honey has been known as a healthy product for human life. Iran has a suitable climate for beekeeping and is among the high-ranked countries in honey production. However, due to failure to comply with quality issues, export of honey from Iran is associated with many problems. According to this issue, this paper presents a robust possibilistic optimization network design model for ...

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...

Possibilistic Defeasible Logic Programming (\Pdelp) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at object-language level. The aim of this paper is twofold: first to present an approach towards extending \Pdelp in order to incorporate fuzzy constants and fuzzy unification, and af...

Answer set programming (ASP) is a form of logic programming in which negation-as-failure is defined in a purely declarative way, based on the notion of a stable model. This short paper briefly explains how a recent generalization of possibilistic logic (GPL) can be used to characterize the semantics of answer set programming. This characterization has several advantages over existing characteri...

Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible argumentation formalism based on an extension of logic programming. Although DeLP has been successfully integrated in a number of different real-world applications, D...

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. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical v...

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. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical v...