where EV represents expected value. In the decision making, the best
way to reflect decision maker's preferences is to express them through
linguistic terms, establishing a semantic correspondence for the different
degrees of feasibility (Zadeh, 1978). Linguistic terms are encountered
in the practical process of data acquisition since human
subjective judgment is involved. Therefore, the decision maker can
choose the preferred credibility levels for constraints based on the linguistic
term scale advanced by Jimenez et al. (2007) (λ = 1: completely
satisfied constraint (SC), λ = 0.9: practically SC, λ = 0.8: almost SC, λ =
0.7: very SC, λ = 0.6: quite SC, λ = 0.5: neither SC nor unsatisfied
constraint). In general, the solution process of the FCCP model can be
summarized as follows: