Individual and Group Replacement Policy under Intuitionistic Fuzzy Environment

Resumen

Physical problems in the universe is modelled mathematically and solved by the suitable
models. Decision makers examine the given problems from quantitative and qualitative
perception. Over the past many decades, in mathematical programming models, such as
linear programming, integer programming and network flow programming, the effects of
uncertainty are unaccountable. Furthermore, decision makers deal with simple optimization
of a utility function, optimization under constraints and optimization in multiple criteria. The
paper the individual and group replacement policies under intuitionistic fuzzy environment
are considered. The necessary theorems are proposed and numerical examples showing the
approach are presented. This paper also gives the comparison of individual and group
replacement models under fuzzy and intuitionistic fuzzy environment. Intuitionistic fuzzy
case provides a better result is justified in this paper.