Automated test assembly (ATA) is a modern approach to test assembly that applies advanced optimization algorithms on computers to build test forms automatically. ATA greatly improves the efficiency and accuracy of the test assembly. This study investigated the effects of the modeling methods and solvers in the mixed‐integer programming (MIP) approach to ATA in the context of assembling parallel linear test forms and multistage testing (MST) panels. The results of two simulation studies indicated that the newly proposed maximin modeling method significantly improved the parallelism of the test information functions (TIFs) among assembled test forms while maintaining relatively high overall TIFs, and the newly proposed binary minimax method considerably reduced the overall discrepancies from the targets. A comparison of four freely available noncommercial MIP solvers from the utilitarian, as opposed to the benchmarking, perspective was also included in this study.