Interval extension of TOPSIS

IV-TOPSIS extends crisp TOPSIS to bounded uncertainty represented as Interval Numbers IN: [L, U]. The Jahanshahloo–Lotfi–Izadikhah (2006) algorithm keeps both bounds throughout normalisation and weighting; the positive- and negative-ideal solutions are then assembled by taking max/min over the appropriate bound depending on whether each criterion is a benefit or a cost. Distances use the opposite bound (lower for d⁺ on benefits, upper for d⁻ on benefits, swapped for costs) so that the worst-case separation is measured. The final relative closeness C* is a crisp scalar in [0, 1] — no defuzzific