Recent progress in additive manufacturing allows for printing customized products with multiple materials and complex geometries. Effectively designing such complex products for optimal performance within the confines of additive manufacturing constraints is challenging, due to the large number of variables in the search space and uncertainties about how the manufacturing processes affect fabricated materials and structures. In this study, characteristics of materials, i.e. Young's modulus (E), ultimate tensile strength (UTS) and density (ρ), for a multi-material inkjet-based 3D-printer are measured experimentally in order to generate data curves for a computational optimization process in configuring multimaterial lattice structures. An optimality criteria method is developed for computationally searching for optimal solutions of a multi-material lattice with fixed topology and truss crosssection sizes using the empirically obtained material measurements. Results demonstrate the feasibility of the approach for optimizing multi-material, lightweight truss structures subject to displacement constraints.