Networked groups of sensors that detect Chemical, Biological, and Radiological (CBR) threats are being developed to defend cities and military bases. Due to the high cost and maintenance of these sensors, the number of sensors deployed is limited. It is vital for the sensors to be deployed in optimal locations for these sensors to be effectively used to analyze the scope of the threat. A genetic algorithm, along with the instantaneous plume prediction capabilities of CT-Analyst has been developed to meet these goals. CT-Analyst’s time dependant plumes, upwind danger zone, and sensor capabilities are used to determine the fitness of sensor networks generated by the genetic algorithm. The optimization and the requirements for the evaluation of sensor networks in an urban region are examined along with the number of sensors required to detect these plumes.