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...

This paper discusses a multi-objective portfolio optimization problem for practical portfolio selection in fuzzy environment, in which the return rates and the turnover rates are characterized by fuzzy variables. Based on the possibility theory, fuzzy return and liquidity are quantified by possibilistic mean, and market risk and liquidity risk are measured by lower possibilistic semivariance. T...

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...

Humanitarian organizations pre-position relief items in pre-disaster and distribute them to the affected areas in post-disaster. Improper planning of emergency operations causes more deaths in post-disaster. In this paper, the problem of relief item pre-positioning and multi-period distribution planning is addressed considering lateral transhipment among distribution centres to improve the effi...

This research proposes a Preemptive Possibilistic Linear Programming (PPLP) approach for solving multiobjective Aggregate Production Planning (APP) problem with interval demand and imprecise unit price and related operating costs. The proposed approach attempts to maximize profit and minimize changes of workforce. It transforms the total profit objective that has imprecise information to three ...

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...

Classical stochastic Markov Decision Processes (MDPs) and possibilistic MDPs ( -MDPs) aim at solving the same kind of problems, involving sequential decision making under uncertainty. The underlying uncertainty model (probabilistic / possibilistic) and preference model (reward / satisfaction degree) change, but the algorithms, based on dynamic programming, are similar. So, a question maybe rais...