A GA-Based Multi-Objective Optimization for Gateway Distribution in a Smart City Bus Network

As smart cities evolve, the efficient and sustainable distribution of communication infrastructure is critical for enabling real-time data sharing, intelligent traffic management, and enhanced passenger experiences. This paper presents a System of Systems Engineering (SoSE)-based ulti-objective optimization framework for the strategic placement of IoT gateways within a bus stop network. Considered optimization objectives are to minimize the number of gateways, balance the load across gateways, maximize network coverage, and ensure that all bus stops locations are covered. The proposed Genetic Algorithm (GA) is designed to handle the complex trade-offs between these objectives, providing a robust solution for real-world deployment scenarios. Simulations are conducted to evaluate the algorithm's performance of different GA parameters. The study enhances the understanding of gateway distribution optimization in smart city transportation networks, supporting urban planners and network designers in improving infrastructure efficiency.