A fuzzy-interval nonlinear programming for boosters under uncertainty

Abstract

Abstract In this paper, an integration of a fuzzy-interval credibility-constrained (FIC) model expressed by fuzzy interval sets (FIS) and interval nonlinear programming (INP), termed an FIC-INP model, was proposed and applied to two cases. After formulating the FIC-INP model, upper and lower disinfection booster costs can be obtained for two cases under various combinations of credibility levels of upper and lower limits. The results indicated that the upper and lower booster costs increased with the credibility levels of the lower limits. The upper as well as the lower booster costs increased with the booster numbers. For credibility levels of lower limit constraints ranging from 0.6 to 0.9, the upper and lower booster costs increased under enlarging/widening trapezoidal distributions, and the intervals of booster costs increased with interval uncertainty. For a lower limit constraint credibility level of 0.5, the upper and lower booster costs decreased under shrinking/narrowing trapezoidal distributions, and the booster cost intervals increased under larger interval trapezoidal distributions. The degrees of effect of the interval uncertainty are higher than the fuzzy uncertainty. The results obtained can provide more information for managers to make booster schemes under fuzzy and interval uncertainties.