Optimization of Electric Bus Scheduling Using Genetic Algorithm: A Case Study in Public Transport of UNNES Campus Area

The transportation service system requires improvements to evolve into a smart and more efficient system. Passengers waiting at bus stops can create long queues, causing a lack of available shuttle bus capacity when arriving at the bus stop. This work proposes a genetic algorithm model to minimize passenger waiting time and schedule shuttle buses to stops with high capacity. The Genetic Algorithm works by searching for the optimal value to result in optimal waiting time by providing calling shuttle bus. After the method reaches the optimal solution, the simulation result will provide a minimum waiting time. In case studies of simulated design at either campus in Central Java, Indonesia. This method provides a simulated system shuttle bus on scheduling to raise a challenge in waiting time efficiency and passenger accumulation at campus transportation. The case studies of the application on passenger waiting time showcase the model's ability to improve transportation services in the unscheduled campus area. This system was designed to ensure that it was effective in addressing the transportation challenges faced by students and staff. Use the full potential of bus transportation in the campus area to ensure continuity between stops and city transportation. Therefore, this approach reduces waiting times and schedules to overcome challenges posed by passenger accumulation for structured campus transportation services. Keywords—Shuttle Bus; Genetic Algorithm; Campus Area; Minimize Waiting Time; Scheduling; Optimization.