We incorporate an arbitrary number of "candidate" positive distinct poles into the scalar l(1) optimization framework in order to obtain low-order rational suboptimal solutions to constrained l(1) optimization problems. Our approach uses a single linear program to minimize an upper bound on the l(1) norm and gives a solution which uses only the best out of the prespecified poles. Rational suboptimal solutions to a scalar two-block problem are obtained similarly.