Computational prediction of ligand-protein binding is an essential part of overcoming the synthesis bottleneck for rapid development of small-molecule drugs. Nevertheless, an accurate prediction of binding free energy is challenging without first establishing a ligand binding pose. Reported in this paper is an advanced optimization algorithm that is capable of providing multiple, high-fidelity solutions to a ligand-protein pose even for complicated systems with large numbers of degrees of freedom. This algorithm achieves high performance by incorporating several important features, such as niching and force-field annealing. Results from several challenging use cases are presented and discussed.