This paper proposes a qualitative approach to solve multicriteria decision making problems under possibilistic uncertainty. Depending on the decision maker attitude with respect to uncertainty (i.e. optimistic or pessimistic) and on her attitude with respect to criteria (i.e. conjunctive or disjunctive), four ex-ante and four ex-post decision rules are defined and investigated. In particular, t...

This paper considers new downside risk-aversion models for linear optimization (linear programming) with discrete fuzzy random variables. Through new downside risk measures for fuzzy stochastic optimization problems, possibilistic low partial moment (PLPM) models are constructed by incorporating possibility and necessity measures into classical low partial moment. To provide practical models, t...

Bayesian games offer a suitable framework for where the utility degrees are additive in essence. This approach does nevertheless not apply to ordinal games, do capture more than ranking, nor situations of decision under qualitative uncertainty. The present paper proposes representation possibilistic incomplete information and extends fundamental notions pure mixed Nash equilibrium this framewor...

This paper is an attempt to cast both uncertainty and time in a logical framework. It generalizes possibilistic logic, previously developed by the authors, where each classical formula is associated with a weight which obeys the laws of possibility theory. In the possibilistic temporal logic we present here, each formula is associated with a time set (a fuzzy set in the more general case) which...

In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management fac...

In possibility theory, there are two kinds of possibilistic causal networks depending if possibilistic conditioning is based on the minimum or on the product operator. Similarly there are also two kinds of possibilistic logic: standard (min-based) possibilistic logic and quantitative (product-based) possibilistic logic. Recently, several equivalent transformations between standard possibilistic...

Gas-fired power plants are commonly employed to deal with the intermittency of renewable energy resources due their flexible characteristics. Therefore, in system transmits gas through gas-fired plants, which makes operation these systems even more interdependent. This study proposes a novel possibilistic model for integrated and presence electric vehicles demand response. The takes into accoun...

General automata are considered with respect to normal-ization over semirings. Possibilistic automata are deened as normal pessimistic fuzzy automata. Possibilistic automata are analogous to stochas-tic automata where stochastic (+=) semirings are replaced by possi-bilistic (_=^) semirings; but where stochastic automata must be normal, fuzzy automata may be (resulting in possibilistic automata)...

The graded possibilistic clustering paradigm includes as the two extreme cases the “probabilistic” assumption and the “possibilistic” assumption adopted by many clustering algorithms. We propose an implementation of a graded possibilistic clustering algorithm based on an interval equality constraint enforcing both the normality condition and the required graded possibilistic condition. Experime...