Inventory problems and the parametric measure $m_λ$
This work addresses inventory management under uncertainty for operations research, but it is incremental as it extends an existing model with a parametric measure.
The authors tackled a risk-neutral multi-item inventory problem with fuzzy demand variables by generalizing a previous credibilistic inventory model using a parametric measure m_λ, and they derived general and specific formulas for optimal solutions, including cases with trapezoidal and triangular fuzzy demands, with numerical applications.
The credibility theory was introduced by B. Liu as a new way to describe the fuzzy uncertainty. The credibility measure is the fundamental notion of the credibility theory. Recently, L.Yang and K. Iwamura extended the credibility measure by defining the parametric measure $m_λ$ ($λ$ is a real parameter in the interval $[0,1]$ and for $λ= 1/2$ we obtain as a particular case the notion of credibility measure). By using the $m_λ$-measure, we studied in this paper a risk neutral multi-item inventory problem. Our construction generalizes the credibilistic inventory model developed by Y. Li and Y. Liu in 2019. In our model, the components of demand vector are fuzzy variables and the maximization problem is formulated by using the notion of $m_λ$-expected value. We shall prove a general formula for the solution of optimization problem, from which we obtained effective formulas for computing the optimal solutions in the particular cases where the demands are trapezoidal and triangular fuzzy numbers. For $λ=1/2$ we obtain as a particular case the computation formulas of the optimal solutions of the credibilistic inventory problem of Li and Liu. These computation formulas are applied for some $m_λ$-models obtained from numerical data.