The optimal placement of samplers and sensors in water distribution systems (WDSs) and wastewater collection systems (WCSs) is fundamental to effective monitoring, early contamination detection, and system protection. The goal of optimal sensor/sampling placement (OSP) is to maximize the ability to detect, monitor, and track critical variables, such as contaminants or temperature, while maintaining cost-effectiveness and operational efficiency. In practice, OSP problems are inherently multi-objective and typically involve trade-offs between cost minimization, spatial and temporal coverage, detection accuracy, and robustness under uncertainty. This paper presents a comprehensive review of recent single- and multi-objective optimization strategies for source detection and monitoring, drawing on approaches developed in various research fields. The reviewed literature is systematically organized according to problem formulation, objective functions, optimization techniques, and decision-making strategies, paying particular attention to their applicability in real-world WDSs and WCSs. Beyond summarizing existing methods, this review critically examines key methodological assumptions and limitations that hinder practical implementation. These include sparse sensor deployment, budget constraints, and modeling and sensor uncertainty. Finally, the paper identifies open challenges and outlines potential directions for future research aimed at improving the robustness, scalability, and practical relevance of OSP strategies.
Yao et al. (Thu,) studied this question.