Sub-Resolution Assist Features (SRAFs) have emerged as a key technology to enable semiconductor manufacturing for advanced technology nodes. SRAF placement is required to adhere to manufacturability constraints (MRC). MRC specifications are distance and size constraints specified by the user to ensure SRAFs are not detrimental to the final target shapes being printed. Conceptually, SRAF placement can be divided into two steps - SRAF candidate generation and SRAF candidate cleanup or conflict resolution. SRAFs generated as candidates may not adhere to MRC constraints. It is during the cleanup/conflict resolution process that the MRC constraints are enforced. In this paper we focus on the latter phase - cleanup. The goal of the cleanup phase is to retain as much of the initial candidates as possible, and, if necessary, transform them to adhere to MRC conditions. An SRAF is said to be in conflict with another shape if it violates the distance MRC constraint. One can model these conflicts using a conflict graph G=(V,E), whose vertices V correspond to geometric shapes involved in a conflict and an edge is present in E, between two vertices if the corresponding shapes are involved in a conflict. A weight is associated with each vertex that could, for example, correspond to area of the corresponding shape. The goal of conflict resolution then, is to find a transformation of the vertices so that the resulting graph is conflict free while maximizing the weight of vertices retained. This can be viewed as a generalization of the computationally hard problem of finding the largest independent set of candidates, albeit allowing for transformation. The transformations we allow include deletion, splitting, resizing, merge, and bounded translation. In this paper, we describe an approach which classifies the conflicts and apply appropriate transformations to achieve effective SRAF placement. Further, we demonstrate that such a strategy reduces the number of rules to be specified by the user, reducing the user effort needed to achieve desirable imaging results.