Optimal scheduling of multiple Sun-synchronous orbit satellites refueling

Abstract The scheduling problem of numerous Sun-synchronous orbit satellites refueling with multiple resupply spacecraft (RSc) considering J 2 perturbation is raised in this paper. Problem scenario indicates that a large number of Sun-synchronous orbit satellites require refueling of different weight, depending on their fuel surplus. We propose a new strategy for the refueling problem, in which the refueling campaign is composed of several independent missions and each mission is carried out by a single RSc. The RSc will transfer between objective satellites so as to refuel them in order. The optimal problem of this strategy can be classified as a Multi-person Traveling Salesman Problem (MTSP). Hence we present a two-step optimization model to solve it, using refueling sequences as design variables and the estimate cost as the objective function. Searching for an initial solution is the first step of optimization, where a database is generated and Branch-and-bound algorithm, Ant Colony System (ACS) are deployed. The second step is to perform local optimization with Simulated Annealing (SA). At last, we give four different numerical examples to evaluate the effectiveness and robustness of this model under different initial conditions, and discuss the impact of these conditions on the optimal results.

[1]  K. Alfriend,et al.  Optimal Servicing of Geosynchronous Satellites , 2002 .

[2]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[3]  S. Dominick,et al.  Orbital test results of a vaned liquid acquisition device , 1994 .

[4]  Martin J. L. Turner,et al.  Rocket and Spacecraft Propulsion: Principles, Practice and New Developments , 2000 .

[5]  E. L. Lawler,et al.  Branch-and-Bound Methods: A Survey , 1966, Oper. Res..

[6]  Geoffrey T. Parks,et al.  Multispacecraft Refueling Optimization Considering the J2 Perturbation and Window Constraints , 2014 .

[7]  Vili Podgorelec,et al.  A survey of genetic algorithms for solving multi depot vehicle routing problem , 2015, Appl. Soft Comput..

[8]  T. Bektaş The multiple traveling salesman problem: an overview of formulations and solution procedures , 2006 .

[9]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[10]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[11]  Ye Yan,et al.  Mission planning optimization for multiple geosynchronous satellites refueling , 2015 .

[12]  Jing Yu,et al.  Optimal mission planning of GEO on-orbit refueling in mixed strategy , 2017 .

[13]  Panagiotis Tsiotras,et al.  Peer-to-Peer Refueling for Circular Satellite Constellations , 2005 .

[14]  Xu Bo,et al.  Research on constellation refueling based on formation flying , 2011 .

[15]  Panagiotis Tsiotras,et al.  A Cooperative P2P Refueling Strategy for Circular Satellite Constellations , 2008 .

[16]  E. Distefano,et al.  Advanced Liquid Feed Experiment , 1993 .

[17]  Ye Yan,et al.  Optimal scheduling of multiple geosynchronous satellites refueling based on a hybrid particle swarm optimizer , 2015 .

[18]  Panagiotis Tsiotras,et al.  Network Flow Formulation for Cooperative Peer-to-Peer Refueling Strategies , 2010 .

[19]  Howard D. Curtis,et al.  Orbital Mechanics for Engineering Students , 2005 .

[20]  Atri Dutta,et al.  Peer-to-Peer Refueling Strategy Using Low-Thrust Propulsion , 2010 .

[21]  Jin Zhang,et al.  LEO cooperative multi-spacecraft refueling mission optimization considering J2 perturbation and target’s surplus propellant constraint , 2017 .