<p>Ballistic and chemical trajectory options to Uranus are investigated for launch dates spanning 50 years. Trajectory solutions are found using STOUR, a patched conic propagator with an analytical ephemeris model. STOUR is heritage software developed by JPL and Purdue, written in FORTRAN. A total of 89 distinct gravity-assist paths to Uranus are considered, most of which will allow for a deep space maneuver (DSM) at some point along the path. For each launch year, the most desirable trajectory is identified and cataloged based on time of flight (up to 15 years), total $\Delta$V cost (DSM and capture maneuver), arrival $V_\infty$, and delivered payload. The Falcon Heavy (Recoverable), Vulcan VC6, Falcon Heavy (Expendable) and SLS Block 1B are considered to provide a range of low- to high-performance launch vehicle capabilities. A rough approximation of Starship's performance capabilities is also computed and applied to select years of launch dates. A flagship mission that delivers both a probe and an orbiter at Uranus is considered, which is approximated as a trajectory capable of delivering 2000 kg. Jupiter is unavailable as a gravity-assist body until the end of the 2020s but alternative gravity-assist paths exist, providing feasible trajectories even in years when Jupiter is not available. A rare Saturn-Uranus alignment in the late 2020's is identified which provides some such trajectory opportunities. A probe-and-orbiter mission to Uranus is feasible for a Vulcan VC6 with approximately 13 year flight times and for a Recoverable Falcon Heavy with approximately 14.5 year flight times. An Expendable Falcon Heavy reduces the time of flight to around 12.5 years and opens up `0E0U' as a gravity-assist path, while the SLS Block 1B typically offers trajectories with 10 to 11 year flight times and opens up more direct `JU' and `U' solutions. With the SLS, flight times as low as 7.5 years are possible.</p> <p>  </p> <p>A new, rapid grid search tool called GREMLINS is also outlined. This new software is capable of solving the same problems as STOUR, but improves on it in three crucial ways: an improved user-experience, more maneuver capabilities, and a more easily maintained and modified code base. GREMLINS takes a different approach to the broad search problem, forgoing $C_3$ matching in favor of using maneuvers to patch together tables of pre-computed Lambert arcs. This approach allows for vectorized computations across data frames of Lambert solutions, which can be computed much more efficiently than the for-loop style approach of past tools. Through the use of SQL tables and a two-step trajectory solving approach, this tool is able to run very quickly while still being able to handle any amount of data required for a broad search. Every line of code in GREMLINS is written in Python in an effort to make it more approachable and easier to develop for a wide community of users, as GREMLINS will be the only only grid search tool available as free and open source software. Multiple example missions and trajectory searches are explored to verify the output from GREMLINS and to compare its performance against STOUR. Despite using a slower coding language, GREMLINS is capable of performing the same trajectory searches in approximately 1/5 the runtime of STOUR, a FORTRAN-coded tool, thanks to its vectorized computations.</p>