Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One ...

mathematical modeling of supply chain operations has proven to be one of the most complex tasks in the field of operations management and operations research. despite the abundance of several modeling proposals in the literature; for vast majority of them, no effective universal application is conceived. this issue renders the proposed mathematical models inapplicable due largely to the fact th...

Abstract: This paper deals with a portfolio selection problem with fuzzy return rates. A possibilistic mean VaR model was proposed for portfolio selection. Specially, we present a mathematical programming model with possibilistic constraint. The possibilistic programming problem can be solved by transforming it into a linear programming problem. A numerical example is given to illustrate the be...

Upper and lower regression models (dual possibilistic models) are proposed for data analysis with crisp inputs and interval or fuzzy outputs. Based on the given data, the dual possibilistic models can be derived from upper and lower directions, respectively, where the inclusion relationship between these two models holds. Thus, the inherent uncertainty existing in the given phenomenon can be ap...

Fuzzy data given by expert knowledge can be regarded as a possibility distribution by which possibilistic linear systems are defined. Recently, it has become important to deal with fuzzy data in connection with expert knowledge. Three formulations of possibilistic linear regression analysis are proposed here to deal with fuzzy data. Since our formulations can be reduced to linear programming pr...

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at object-language level. This paper presents a first approach towards extending P-DeLP to incorporate fuzzy constants and fuzzy propositional variables. We focus on how to characteri...

Vast pools of historical financial information are available on economies, industry, and individual companies that affect investors’ selection of appropriate portfolios. Fuzzy data provides a good tool to reflect investors’ opinions based on this information. A possibilistic mean variance safety-first portfolio selection model is developed to support investors’ decision making, to take into con...

12 Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from 13 argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-lan14 guage level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot 15 be expressed in the object la...

Portfolio selection is an important issue for researchers and practitioners. Compared with the conventional probabilistic mean-variance method, fuzzy number can better describe an uncertain environment with vagueness and ambiguity. In this paper, the portfolio selection model with transaction costs and lending is proposed by means of possibilistic mean and possibilistic variance under the assum...