People Movement-driven Dynamic Bus Routing Problem with Route Similarity Maximization

In the era of Industry 4.0, utilizing big data to make real-time decisions becomes possible. In the mobility and trans- portation area, including public transportation services, innovative practices could be incorporated to make better de- cisions for the system and its users. This study proposes a novel dynamic bus routing model. In the proposed mathe- matical formulation, previous bus routes are considered when designing new routes while minimizing the changes in the routes. Such a decision on minimizing the changes is made to provide a better experience by the bus passengers. In the numerical experiments, various data sets are solved. This study could be an initial study for the next studies to discover other potential problems to solve within the context of big data and Industry 4.0.