REACTIVE TABU SEARCH AND SENSOR SELECTION IN ACTIVE STRUCTURAL ACOUSTIC CONTROL-PROBLEMS

A Reactive Tabu Search (RTS) is examined. In addition to a dynamic tab u tenure RTS also detects when the search has entered an unproductive area and restarts RTS based on distinctive features of the unproductiv e area. We explore the effectiveness of RTS over a static tabu list (o f a kind used in many implementations) for a two variable unconstraine d discrete optimization model with 9 nearly identical minima and 513 o ther local minima. One of the key features of this problem is that the two-dimensional domain allows us to provide graphical descriptions of the performance of RTS. We then apply RTS to a sensor selection probl em in active structural acoustic control. The objective in this proble m is to select a set of 8 sensors out of 462 potential sensor location s so that the noise measured at the 8 chosen sensors is as close as po ssible to the noise measured at all 462. Computational experiments for data taken from a laboratory test article at NASA Langley Research Ce nter are provided.