Smart city applications in the Big Data era require not only techniques dedicated to dynamicity handling, but also the ability to take into account contextual information, user preferences and requirements, and real-time events to provide optimal solutions and automatic configuration for the end user. In this paper, we present a specific functionality in the design and implementation of a declarative decision support component that exploits contextual information, user preferences and requirements to automatically provide optimal configurations of smart city applications. The key property of user-centricity of our approach is achieved by enabling users to declaratively specify constraints and preferences on the solutions provided by the smart city application through the Decision Support component, and automatically map these constraints and preferences to provide optimal responses targeting user needs. We showcase the effectiveness and flexibility of our solution in two real usecase scenarios: a multimodal travel planner and a mobile parking application. All the components and algorithms described in this paper have been defined and implemented as part of the Smart City Framework CityPulse (www.ict-citypulse.eu).