Interval methods is one option for managing uncertainty in optimization problems and in decision management. The precise numerical estimation of coefficients may be meaningless in real-world applications, because data sources are often uncertain, vague and incomplete. In this paper we introduce a comparison index for interval ordering based on the generalized Hukuhara difference; we show that the new index includes the commonly used order relations proposed in literature. The definition of a risk measure guarantees the possibility to quantify a worst-case loss when solving maximization or minimization problems with intervals.
M.L. Guerra, L.Stefanini (2012). A comparison index for interval ordering based on generalized Hukuhara difference. SOFT COMPUTING, 16,11, 1931-1943 [10.1007/s00500-012-0866-9].
A comparison index for interval ordering based on generalized Hukuhara difference
GUERRA, MARIA LETIZIA;
2012
Abstract
Interval methods is one option for managing uncertainty in optimization problems and in decision management. The precise numerical estimation of coefficients may be meaningless in real-world applications, because data sources are often uncertain, vague and incomplete. In this paper we introduce a comparison index for interval ordering based on the generalized Hukuhara difference; we show that the new index includes the commonly used order relations proposed in literature. The definition of a risk measure guarantees the possibility to quantify a worst-case loss when solving maximization or minimization problems with intervals.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
