Minimizing the cost of availability of services from a constellation of satellites

A model was developed to allow the minimization of life cycle cost of a system providing availability of services from a constellation of satellites. The performance of local optimization techniques (simplex and complex) was evaluated against global optimization techniques (Simulated Annealing and Genetic Algorithms). The global optimization techniques performed much better with Genetic Algorithms slightly better. Three services were evaluated, availability of n satellite coverage, navigation accuracy, and satellite network connectivity. The performance of the global optimization technique was compared to both heuristic and local optimization techniques currently used. The model consists of a cost model, and a performance model. The cost model includes the cost of purchasing and maintaining an inventory of satellites and launch vehicles, launch operations, and on orbit operations. The performance model evaluates the availability over geographic grid averaging areas over a given period of time. It includes the effects of satellite outages and replenishment strategy including the use of active or in-active spares, multiple satellites per launch vehicle. Depending on the definition of service availability and service the global optimization techniques were able to reduce the life cycle cost from 2% up to 17% (64–436 M{dollar}) over the heuristic and local optimization techniques.