public class Cobylaextends ObjectConstrained Optimization BY Linear Approximation in Java. COBYLA2 is an implementation of Powell\xc3\x83\xc2\x83\xc3\x82\xc2\xa2\xc3\x83\xc2\x82\xc3\x82\xc2\x80\xc3\x83\xc2\x82\xc3\x82\xc2\x99s nonlinear derivative-free constrained optimization that uses a linear approximation approach. The algorithm is a sequential trust-region algorithm that employs linear approximations to the objective and constraint functions, where the approximations are formed by linear interpolation at n+1 points in the space of the variables and tries to maintain a regular-shaped simplex over iterations. It solves nonsmooth NLP with a moderate number of variables (about 100). Inequality constraints only. The initial point X is taken as one vertex of the initial simplex with zero being another, so, X should not be entered as the zero vector.