This paper presents a novel technique that enhances the general precedence, mixed-integer programming approach for the optimal scheduling of process operations. It proves to effectively solve different types of industrial problems dealing with particular sequence-dependent issues, requiring less computational effort than other optimization models. The new formulation takes advantage of the general precedence modeling efficiency, overcoming one of its major limitations.