The goal of the high level synthesis process for real time applications is to minimize the implementation cost, while still satisfying all timing constraints. In this paper, the authors present a combination of four conceptually simple, yet powerful, transformations: namely retiming, associativity, commutativity and inverse element law, which can help to further this goal. Since the minimization problem associated with these transformations is NP complete, a new fast iterative improvement probabilistic algorithm has been developed. The effectiveness of the proposed algorithm and the associated transformations is demonstrated in multiple ways: using standard benchmark examples, with the aid of statistical analysis and through a comparison with estimated minimal bounds.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>