Searching for a Target Traveling between a Hiding Area and an Operating Area over Multiple Routes

We consider the problem of searching for a target that moves between a hiding area and an operating area over multiple fixed routes. The search is carried out with one or more cookie-cutter sensors, which can detect the target instantly once the target comes within the detection radius of the sensor. In the hiding area, the target is shielded from being detected. The residence times of the target, respectively, in the hiding area and in the operating area, are exponentially distributed. These dwell times are mathematically described by Markov transition rates. The decision of which route the target will take on each travel to and back from the operating area is governed by a probability distribution. We study the mathematical formulation of this search problem and analytically solve for the mean time to detection. Based on the mean time to capture, we evaluate the performance of placing the searcher(s) to monitor various travel route(s) or to scan the operating area. The optimal search design is the one that minimizes the mean time to detection. We find that in many situations the optimal search design is not the one suggested by the straightforward intuition. Our analytical results can provide operational guidances to homeland security, military, and law enforcement applications.

Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy

Flexible AC transmission systems(FACTS)devices can effectively optimize the distribution of power flow.Power flow entropy can be applied as a measure of load distribution.In this paper,a method is proposed to optimize the distribution of power flow with the coordination of multi-type FACTS devices and establishes the corresponding mathematical models.The modified group searcher optimization(GSO)algorithm is proposed,in which the angle search is combined with chaotic search model to avoid jumping into local optimization.Compared with the different optimal allocation of multi-FACTS devices,the optimal allocation of multi-FACTS devices is achieved under the economic constraints.The locations obtained by this method can achieve the purpose of balancing power flow and enhancing the system performances.The simulations are demonstrated in an IEEE 118-bus power system with two classical types of FACTS,namely static var compensator(SVC)and thyristor controlled series Compensator(TCSC).The simulation results show that the proposed method is feasible and effective.