The authors describe an iterative method for the approximate solution of nondifferentiable convex programming problems. The problems incorporate linear equality and inequality constraints \((Ax=b\), \(x\geq 0)\); the method combines Wolfe's well-known reduced gradient algorithm with the bundle method of nonsmooth optimization. The algorithm is explained clearly, convergence is proved, and five numerical examples are presented.