With the globalization of markets and increasing concerns on environmental sustainability, complexities of selecting green suppliers have increased substantially. Since 1980s, several mathematical models have been proposed, but few of them paid attention to economic, environmental and geographical elements simultaneously. This research presents a new approach to supplier selection and thus network design that makes use of Geographical Information Systems (GIS) and mathematical programming in a synergistic and hierarchical way. In the first stage, using GIS spatial data and World Bank country performance indices, a subset of countries is selected. In the second stage, a multi-objective mixed-integer programming model is used to help the management select suitable suppliers and allocate the optimum order quantities, considering optimizing costs, carbon footprint, quality and delivery reliability. Budget, demand, suppliers’ capacity, and carbon emission cap constraints are also considered. These two stages are implemented in a user-friendly software using existing open-source technologies, i.e., WorldWind for GIS spatial data information and geo-mapping of facility locations. With the implementation of this system, companies can efficiently design supply chain networks objectively and in a visual manner. The developed method along with the software implementation is shown on a bicycle manufacturing supplier selection.