In this paper, an analysis of the convergence performance is conducted for a class of possibilistic clustering algorithms utilizing the Zangwill convergence theorem. It is shown that under certain conditions the iterative sequence generated by a possibilistic clustering algorithm converges, at least along a subsequence, to either a local minimizer or a saddle point of the objective function of ...

Providing an efficient production plan that integrates the procurement and distribution plans into a unified framework is critical to achieving competitive advantage. In this paper,we consider a supply chainmaster planningmodel consisting ofmultiple suppliers, one manufacturer andmultiple distribution centers.Wefirst propose a newmulti-objective possibilisticmixed integer linear programming mod...

This study proposes a bi-objective mixed possibilistic, two-stage stochastic programming model to address supplier selection and order allocation problem to build the resilient supply base under operational and disruption risks. The model accounts for epistemic uncertainty of critical data and applies several proactive strategies such as suppliers’ business continuity plans, fortification of su...

This paper considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. A new decision making model optimizing possibilistic value at risk (pVaR) is proposed by incorporating the concept of value at risk (VaR) into possibility theory. It is shown that the original MOLPPs involving random fuzzy variables are trans...

This paper deals with the stock portfolio selection problem involved trapezoidal fuzzy number returns and multiple mental accounts. A behavioral decision model is proposed to maximize possibilistic mean value of return ensure each account exceeding given minimum aspiration level a probability. Then, some programming models are designed solve optimal strategy. Finally, one numerical example illu...

The aim of this paper is to develop an interactive two-phase method that can help the Project Manager (PM) with solving the fuzzy multi-objective decision problems. Therefore, in this paper, we first revisit the related papers and focus on how to develop an interactive two-phase method. Next, we establish to consider the imprecise nature of the data by fulfilling the possibilistic programming m...

Khatter (Soft Comput 24:6847–16,867, 2020) pointed out that although several approaches are proposed in the literature to solve single-valued neutrosophic linear programming problems (SVNLPPS) (linear which all parameters except decision variables either represented by triangular numbers (SVTNNS) or trapezoidal (SVTrNNS)). However, methods for comparing (SVNNS), used existing approaches, indepe...

This paper considers a portfolio selection problem with type-2 fuzzy future returns involving ambiguous and subjectivity. Since this proposed problem is not well-defined due to fuzziness, introducing the fuzzy goal for the total future return and the degree of possibility, the main problem is transformed into the standard fuzzy programming problem including the secondary fuzzy numbers. Furtherm...

The handling of exceptions in multiclass problems is a tricky issue in inductive logic programming (ILP). In this paper we propose a new formalization of the ILP problem which accounts for default reasoning, and is encoded with first-order possibilistic logic. We show that this formalization allows us to handle rules with exceptions, and to prevent an example to be classified in more than one c...