The issue of write-read contention is one of the most prevalent problems when deploying real-time data warehouses. With increasing load, updates are increasingly delayed and previously fast queries tend to be slowed down considerably. However, depending on the user requirements, we can improve the response time or the data quality by scheduling the queries and updates appropriately. If both criteria are to be considered simultaneously, we are faced with a so-called multi-objective optimization problem. We transformed this problem into a knapsack problem with additional inequalities and solved it efficiently. Based on our solution, we developed a scheduling approach that provides the optimal schedule with regard to the user requirements at any given point in time. We evaluated our scheduling in an extensive experimental study, where we compared our approach with the respective optimal schedule policies of each single optimization objective.