A Genetic Algorithm Model for Mission Planning and Dynamic Resource Allocation of Airborne Sensors

Genetic Algorithms (GA) have been very successful in combinatorially{explosive problems such as; Job Shop Scheduling, Non-linear Transportation Model, and the Traveling Salesman Problem. The problem of mission planning for large numbers of airborne platforms contains elements of all three of these classic GA problems. This paper will outline the application of genetic algorithms to mission planning and dynamic allocation of airborne sensors. An experiment will consist of a mission simulation containing (n) airborne sensors in diierent locations and states of readiness, and (m) requests for imagery with varying mission priorities. The GA will match sensors with requests in order to minimize the cost and time{line and maximize the execution of high priority requests. Results of simulation will be discussed.

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