This paper presents a novel approach for post-mapping optimization. We exploit the concept of generalized matching, a technique that nds symbolically all possible matching assignments of library cells to a multi-output network speci ed by a Boolean relation. Several objectives are targeted: area minimization under delay constraints, power minimization under delay constraints and unconstrained delay minimization. We describe the theory of generalized matching and the algorithmic optimization required for its e cient and robust implementation. A tool based on generalized matching has been implemented and tested on large examples of the MCNC'91 benchmark suite. We obtain sizable improvements in: i speed 6 in average, up to 20.7; ii area under speed constraints 13.7 in average, up to 29.5 and iii power under speed constraints 22.3 in average, up to 38.1.