Constraint Programming based multi-objective sensor network design for fault diagnosis

Optimal placement of sensors based on different criteria viz., precision, reliability, cost, and fault unobservability has been an important area of research in the last few years. Most of the sensor location problems proposed in literature have been solved either using graph theoretic approaches or conventional mathematical optimization techniques. However, these techniques have not been able to satisfactorily address the issue of tradeoffs between multiple objectives, the determination of which is important from a designer’s perspective in terms of providing design flexibility. In this article, we address this challenge by proposing the use of Constraint Programming (CP) as a potential alternative to conventional solution techniques to determine the pareto optimal solutions. CP is an intelligent enumeration based optimization technique that uses domain reduction as its inference engine and has recently emerged as a powerful tool for solving combinatorial optimization problem in operations research. We also present efficient reformulation of some existing problems using the superior modelling power of CP.