Double description method over the field of algebraic numbers

We consider the problem of constructing the dual representation of a convex polyhedron defined as a set of solutions to a system of linear inequalities with coefficients which are algebraic numbers. The inverse problem is equivalent (dual) to the initial problem. We propose program implementations of several variations of the well-known double description method (Motzkin–Burger method) solving this problem. The following two cases are considered: 1) the elements of the system of inequalities are arbitrary algebraic numbers, and each such number is represented by its minimal polynomial and a localizing interval; 2) the elements of the system belong to a given extension ${\mathbb Q} (\alpha)$ of ${\mathbb Q}$, and the minimal polynomial and the localizing interval are given only for $\alpha$, all elements of the system, intermediate and final results are represented as polynomials of $\alpha$. As expected, the program implementation for the second case significantly outperforms the implementation for the first one in terms of speed. In the second case, for greater acceleration, we suggest using a Boolean matrix instead of the discrepancy matrix. The results of a computational experiment show that the program is quite suitable for solving medium-scale problems.