Battery electric buses (BEBs) are recognised as sustainable modes of transportation. Because of its increasing range, efficient and convenient overnight charging has become crucial. The limited number of charging stations and variability in setup times require the optimisation of BEB charging schedules. This study proposes an optimal overnight centralised charging schedule that considers setup time and battery-degradation costs. We model this as a multi-travelling salesman problem with sojourn time to minimise operating costs, including electricity, setup time, and battery wear, while adhering to the bus-schedule constraints. We introduce a local search grouping genetic algorithm with a 2-opt operator local search to address the complexities of public-transport networks. Our extensive numerical analysis, grounded in real-world data, shows a 4.48% reduction in operating costs using our optimised strategy compared with current methods. Moreover, our charging-station allocation analysis provides insights for resource optimisation, advancing sustainable public transport, and charging strategies. This study contributes to the field of sustainable public transportation and charging optimisation.