A good measurement system improves capability to identify the behavior of civil engineering structures. This paper presents a measurement-system design approach for continuous monitoring of structures. This approach performs two tasks: (1) determining the appropriate number of sensors to be employed and (2) placing the sensors in the most informative locations. Measurement systems are designed using three criteria: minimize the number of non-detectable scenarios, minimize the average time to detection and maximize damage detectability. To select the best compromise solution in the solution set obtained from multi-objective optimization, two multi-criteria decision-making methods, Pareto-Edgeworth-Grierson multi-criteria decision-making (PEG-MCDM) and Preference Ranking Organization METhod for Enrichment Evaluation (PROMETHEE), are employed. A railway truss bridge in Zangenberg (Germany) is used as a case study where measurement data are interpreted using a model-free (non-physics based) method - Moving Principal Component Analysis (MPCA). Results demonstrate that the proposed approach is able to provide engineers with measurement-system-design support for continuous monitoring of structures.