
The paper deals with stability in multiobjective nonlinear programming. Considering some earlier works by Luhandjula and the same author, Kassem tried to expand the concepts for possibilistic stability analysis in multiobjective optimization. Unfortunately, there are a lot of nebulosities in this article. The author does not really apply the concept of a-possibility efficient solutions introduced by \textit{M. K. Luhandjula} (Definition 4 in the article, cf. Definition 5 in [ibid. 21, 135-145 (1987; Zbl 0621.90085)] for the case of multiobjective maximization). The terms efficiency or set of efficient solutions are not defined at all, and there are many indications that the author has a wrong perception of it, i.e. assuming the uniqueness of an efficient solution. On many occasions, \(\min F(x,t)\) is used as if it were a vector and not a set a vectors. Since the concepts of efficiency and a-possibility efficiency are central to all other stability concepts, it is hard to say more about the value of the paper.
random variables, Sensitivity, stability, parametric optimization, parametric programming, Fuzzy and other nonstochastic uncertainty mathematical programming, multiobjective nonlinear programming, stability, Multi-objective and goal programming
random variables, Sensitivity, stability, parametric optimization, parametric programming, Fuzzy and other nonstochastic uncertainty mathematical programming, multiobjective nonlinear programming, stability, Multi-objective and goal programming
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