Optimal Intervisibility Site Selection

Optimal placement of multiple sensors is an important part of the contemporary battlefield, however the computational challenge increases exponentially with the number of sensors considered in the problem. Global search techniques such as Simulated Annealing and Genetic Algorithms have been employed with success against such problems. Toyon proposes to develop and compare two optimization methods, Simulated Annealing and Genetic Algorithm to provide a timely near-optimal multiple sensor placement solution. By leveraging the Geospatial Analysis and Planning Support (GAPS) Toolbox, Toyon begins from an operationally deployed GIS application with an optimization module already developed. This proposal presents case study results for the existing Simulated Annealing approach and three techniques that show promise in minimizing the time to achieve a solution. Our Genetic Algorithm approach utilizes efficient storage and processing techniques that show promise with initial testing. Phase I deliverables will include a demonstration of the visibility optimizers against 1200 x 1200 cell urban and rural terrains, comparison results, and a standalone executable. Phase II will advance the optimization method and develop the capability as a web service application capable of interfacing with the Commercial Joint Mapping Toolkit environment.