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Such uncertainty and constraints in objectives can also be seen in security patrolling, trip planning, and network maintenance. We target the problem of multi-agent scheduling with bounded objectives. The scheduling aims for maximum road network coverage while ensuring sufficient visits to particular road segments for defect identification of an uncertain subject, such as potholes and faded markings during road inspection or crimes and parking violations during security patrolling. We leverage an approximate bi-objective algorithm and propose a hierarchical circular route-planning algorithm. Our approach maximizes the road coverage among robots and decreases the search space when maximizing defect identification. We evaluate our approach on four real-world datasets. 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