When optimizing FFParams, usually the bonded interactions are fitted to quantum mechanic (QM) calculations of energies, frequencies and structures, while the van der Waals (vdW) parameters are optimized towards experimental quantities like densities or heat of vaporization . The electrostatic terms are typically parameterized to reproduce QM electrostatic potentials or energies of water-molecule interactions . Many of the available FFParams optimization methods are either not automated or treat the optimization objectives sequentially, instead of simultaneously. To address the latter, we introduced a multiscale optimization workflow that simultaneously optimizes Lennard-Jones parameters (LJParams) (i.e. σ C , σ H , C and H ) towards different property domains (i.e. single-molecule or atomistic properties and multi-molecular properties) . It was shown that the relative conformational energies (RCE) reproduction of n-octane could be significantly improved with a minimal reduction in the accuracy of its bulk-phase density. Herein, a modified approach is presented that provides more control over the balancing of the optimized properties, improving the accuracy of the density calculations, while maintaining the RCE reproduction quality. This is achieved by a non-linear projection (NLP) of the individual property-specific parts of objective function and adapting their weighting factors (WFs). Four different approaches are investigated to determine the intra-domain WFs (i.e. those used within the same property domain). Additionally, inter-domain property balancing is introduced. Using this technique, the balance between the various properties subject to optimization is finely tuned. Both intra-and inter-domain balancing are combined with the NLP approach of the loss function's components. Finally, we present the best set of optimized FFParams, improving the previously achieved results . We also show that different weighting factors result in different parameter sets, corresponding to different minima in the objective function landscape, indicating that FFParams optimization not only is a multiobjective but also a multi-modal problem and should be treated as such.