Seo, JahoBaghyari, Farhad2024-06-112024-06-112024-04-01https://hdl.handle.net/10155/1769Snowplowing and sweeping are essential services to municipalities, which affect travel safety, environment protection, and health to residents. To provide acceptable quality services, route optimization is one of the key strategies that allow for enhancing efficiency, saving costs, and balancing workloads among operational teams. In order to address this issue and reflect on recent research trends in routing problems that require variable conditions and real-time events, this study proposes two heuristic methods: Smart Selective Navigator and a two-stage algorithm for real-time scheduling and route generation. Through two major case studies — winter operations in the City of Oshawa and autonomous street sweeping in Uchi Park —the proposed methods demonstrate superior performance in generating optimal routes that satisfy complex constraints such as turn restrictions and supply limits and handle real-time events like vehicle breakdowns.enRoute generationReal-timeSnowplowingArc routing problemSchedulingThesis