A deterministic approach to linear programs with several additional multiplicative constraints

We consider a global optimization problem of minimizing a linear function s ubject to p linear multiplicative constraints as well as ordinary linear co nstraints. We show that this problem can reduce to a 2p-dimensional reverse convex program, and present an algorithm for solving the resulting problem . Our algorithm converges to a globally optimal solution and yields an epsi lon-approximate solution in finite time for any epsilon > 0. We also report some results of computational experiment.