Global optimization of Pd-Au bimetallic clusters in the size range N = 2-50 has been performed using a genetic algorithm, coupled with the Gupta many-body empirical potential (EP) to model interatomic interactions. Three sets of EP parameters have been examined in this work: (a) an average of pure Pd and Au parameters, (b) experimental Pd-Au-fitted parameters, and (c) DFT-fitted parameters. Stability criteria, such as binding energy and second difference in energy, have been used to determine the lowest energy structures, that is., the global minima (GM). DFT local relaxations have been performed on all the "putative" GM Structures for 1: 1 compositions of (Pd-AU)(N/2) up to N = 50 for the three sets of EP parameters. It is found that the average parameter set a leads to a PdcoreAushell segregation, whereas the fitted parameter sets b and c lead to more Pd-Au mixing. DFT reoptimization of the structures produced by potentials a, b, and c shows small differences in binding energies. In addition, 34- and 38-atom Pd-Au clusters were studied using these three Gupta potential parametrizations as a function of composition and analyzed in terms of their mixing energies and chemical order parameters. DFT relaxations were performed on the lowest mixing energy compositions, allowing us to have a clearer description of the energy landscape for all three EP parameter sets at these cluster sizes. For the compositions, Pd17Au17 and Pd19Au19, DFT calculations confirm that some degree of Au surface segregation is energetically preferred, though it is not necessarily complete PdcoreAushell segregation, as predicted by the average potential a.