Optimal scheduling of multiple geosynchronous satellites refueling based on a hybrid particle swarm optimizer

Abstract

A new multiple geosynchronous satellites refueling strategy, where multiple servicing satellites and fuel stations are utilized to refuel multiple geosynchronous satellites of known fuel demand is proposed in this paper. Each servicing satellite can carry a limited amount of fuel. Servicing satellites and fuel stations initially are parked in the geosynchronous Earth orbit (GEO). Servicing satellites are employed to distribute the fuel stored in fuel stations to fuel-deficient GEO targets and the goal is to find a set of optimal planning schemes with a minimum fuel cost. The multiple geosynchronous satellites refueling problem (MGSRP) is NP-hard and this study puts forward a two-level optimization approach to solve this problem. The up-level optimization uses refueling order X, decision variable S as design variables, and they are optimized by a hybrid particle swarm optimization (HPSO) algorithm. The low-level optimization uses decision variable R as design variable, and employs the exhaustive search (ES) to find the optimal solution. Finally, two numerical examples are presented to demonstrate the effectiveness of the approach for mission planning of multiple geosynchronous satellites refueling.