| Exact and approximate route set generation for resilient partial observability in sensor location problems |
| English |
| Rinaldi, Marco  [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit] |
| Viti, Francesco [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit] |
| 2017 |
| Transportation Research. Part B : Methodological |
| Elsevier Ltd |
| 105 |
| 86-119 |
| Yes (verified by ORBilu) |
| 0191-2615 |
| [en] Genetic algorithm ; Maximum clique problem ; Network Sensor Location Problem |
| [en] Sensor positioning is a fundamental problem in transportation networks, as the location of sensors strongly determines how traffic flows are observable and hence manageable. This paper aims to develop a methodology to determine sensor locations on a network such that an optimal trade-off solution is found between the amount of sensors installed and the resilience of the sensor set. In particular, we propose exact and heuristic solutions for identifying the optimal route sets such that no other route would include any additional information for finding optimal full and partial observability solutions. This is an important contribution to sensor location problems, as route-based link flow inference problems have non-unique solutions, strongly depending on the used link-route information. The properties of the new methodology are analyzed and illustrated through different case studies, and the advantages of the algorithms are quantified both for full and for partial observability solutions. Due to the route sets found by our approach, we are able to find full observability solutions characterized by a small number of sensors, while yet being efficient also in terms of partial observability. We perform validation tests on both small and real-life sized network instances. © 2017 Elsevier Ltd |
| http://hdl.handle.net/10993/33449 |
| 10.1016/j.trb.2017.08.007 |
