A NEW BIVARIATE GENERALIZED EXPONENTIAL DISTRIBUTION WITH APPLICATION IN JOINT CHANCE-CONSTRAINED PROGRAMMING
Rasha Ebaid, Afaf El-Dash · Far East Journal of Mathematical Sciences (FJMS) · 2021
The generalized exponential distribution has many nice properties and has proven great efficiency at modeling lifetime data. In this paper we propose a new bivariate generalized exponential distribution with generalized exponential marginals using the Cuadras-Augé copula. Several properties of the new distribution are discussed. The new bivariate distribution is then used to model the dependence structure in random right-hand-side parameters of a joint chance-constrained model. Transformation of the probabilistic model to an equivalent deterministic concave model is presented which is then approximated to a linear programming model. Finally, a numerical example is given to illustrate the transformation and approximation steps.