The probabilities with which a genetic algorithm applies its operators have sometimes been set adaptively; information derived from the algorithm's performance has been used to revise the probabilities as the GA runs. This paper reviews one such mechanism, which assigns probabilities to crossover and mutation, and extends it to assign probabilities to three or more operators. The extension guarantees that no operator will be excluded, even if it has recently been ineffective. Several versions of the extended mechanism are tested in a steady-state GA for the rectilinear Steiner problem, in which we seek a tree of minimum length, made up of horizontal and vertical line segments, that connects a set of given points. The coding chosen for the trees gives rise to three genetic operators, a crossover and two mutations. The operator probabilities develop in interesting ways, but the algorithm itself never identifies trees shorter than those found by the same GA with fixed operator probabilities. This raises questions about how information available to a GA as it runs can be used to adjust its parameters and improve its performance.