Long-haul freight transportation forms the backbone of global supply chains and involves diverse types of carriers, e.g., liner shipping companies, rail freight operators, less-than-truckload carriers, express parcel companies, etc. Planning decisions across these applications can be assisted by solving the Scheduled Service Network Design Problem, a fundamental but computationally challenging optimization problem. However, most instances used in the literature are not accessible, and the few available benchmarks were not designed to reflect the structural properties of real-world freight transportation networks. To fill this gap, we introduce a new open-source generator of instances for the Scheduled Service Network Design Problem. Our generator leverages insights from Complex Network Analysis to reproduce key structural features of freight transportation networks, while allowing users to tune parameters to generate diversified instances. A computational study validates its ability to produce networks exhibiting metrics aligned with those of networks derived from existing freight applications. We also include features such as preprocessing rules, varied demand pattern generation, and network emulation to increase the value of our tool for both practitioners and researchers.