Numerical optimization is a common technique in various areas of computational chemistry, molecular modeling and drug design. It is a key element of 3D techniques, for example, the optimization of protein–ligand poses and small-molecule conformers. Here, often the BFGS algorithm or variants thereof are used. However, the BFGS algorithm tends to make unreasonable large changes to the optimized system under certain circumstances. This behavior has been known for a long time and different solutions have been suggested. Recently, we have analyzed the optimization behavior of our novel JAMDA scoring function in detail and proposed the limited step length (LSL)-BFGS algorithm as a new solution to the problem of excessively large steps during optimization. The LSL-BFGS algorithm allows to control the step sizes during optimization. Its unique feature is the inclusion of arbitrary domain knowledge into the selection of the step sizes. Here, we introduce the open-source LSLOpt C++ library that implements this LSL-BFGS algorithm and demonstrate its usage.