637
Views
22
CrossRef citations to date
0
Altmetric
Original Articles

A new hybrid genetic algorithm for the collection scheduling problem for a satellite constellation

&
Pages 1390-1410 | Received 23 Oct 2018, Accepted 13 Apr 2019, Published online: 26 Jun 2019

References

  • Agnese, J. C., & Bensana, E. (1995). Exact and approximate methods for the daily management of an earth observation satellite. Proceeding of the fifth ESA workshop on artificial intelligence and knowledge based systems for space.
  • Augenstein, S., Estanislao, A., Guere, E., & Blaes, S. (2016). Optimal scheduling of a constellation of earth-imaging satellites, for maximal data throughput and efficient human management. Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling.
  • Baek, S.-W., Han, S.-M., Cho, K.-R., Lee, D.-W., Yang, J.-S., Bainum, P.-M., & Kim, H.-D. (2011). Development of a scheduling algorithm and GUI for autonomous satellite missions. Acta Astronautica, 68(7–8), 1396–1402. doi:10.1016/j.actaastro.2010.08.011
  • Barbulescu, L., Watson, J.-P., Whitley, L. D., & Howe, A. E. (2004). Scheduling space-ground communications for the air force satellite control network. Journal of Scheduling, 7(1), 7–34. doi:10.1023/B:JOSH.0000013053.32600.3c
  • Benoist, T., & Rottembourg, B. (2004). Upper bounds for revenue maximization in a satellite scheduling problem. Quarterly Journal of the Belgian, French and Italian Operations Research Societies, 2(3), 235–249. doi:10.1007/s10288-004-0044-8
  • Bensana, E., Verfaillie, G., Agnese, J. C., Bataille, N., & Blumestein, D. (1996). Exact and inexact methods for the daily management of an earth observation satellite. Proceeding of the international symposium on space mission operations and ground data systems, 4, pp. 507–514.
  • Berger, J., Barkaoui, M., & Boukhtouta, A. (2007). A hybrid genetic approach for airborne sensor vehicle routing in real-time reconnaissance missions. Journal of Aerospace Science and Technology, 11(4), 317–326. Volume Issue doi:10.1016/j.ast.2006.12.006
  • Bianchessi, N., Cordeau, J. F., Desrosiers, J., Laporte, G., & Raymond, V. (2007). A heuristic for the multi-satellite, multi-orbit and multi-user management of earth observation satellites. European Journal of Operational Research, 177(2), 750–762. doi:10.1016/j.ejor.2005.12.026
  • Bianchessi, N., Piuoi, V., Righini, G., Roveri, M., Laneve, G., & Zigrino, A. (2004). An optimization approach to the planning of earth observing satellites. Proceeding of the fourth international workshop on planning and scheduling for space (IWPSS’04).
  • Bianchessi, N., & Righini, G. (2006). A mathematical programming algorithm for planning and scheduling an earth observing SAR constellation. Proceeding of the fifth international workshop on planning and scheduling for space (IWPSS’06).
  • Bianchessi, N., & Righini, G. (2008). Planning and scheduling algorithms for the COSMOSkyMed constellation. Aerospace Science and Technology, 12(7), 535–544. doi:10.1016/j.ast.2008.01.001
  • Butler, P. J. (2005). Project polar epsilon: Joint space-based wide area surveillance and support capability. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing, Symposium (IGARSS), Vol. 2, pp. 1194.
  • Chen, X., Reinelt, G., Dai, G., & Wang, M. (2018). Priority-based and conflict-avoidance heuristics for multi-satellite scheduling. Applied Soft Computing, 69, 177–191. doi:10.1016/j.asoc.2018.04.021
  • Chu, X., Chen, Y., & Lining, X. (2017a). A branch and bound algorithm for agile earth observation satellite scheduling. Discrete Dynamics in Nature and Society, 2017, 1. Article ID 7345941, doi:10.1155/2017/7345941
  • Chu, X., Chen, Y., & Tan, Y. (2017b). An anytime branch and bound algorithm for agile earth observation satellite onboard scheduling. Advances in Space Research, 60(9), 2077–2090. doi:10.1016/j.asr.2017.07.026
  • Gabrel, V. (2006). Strengthened 0-1 linear formulation for the daily satellite mission planning. Journal of Combinatorial Optimization, 11(3), 341–346. doi:10.1007/s10878-006-7912-4
  • Gabrel, V., Moulet, A., Murat, C., & Paschos, V. T. (1997). A new single model and derived algorithms for the satellite shot planning problem using graph theory concepts. Annals of Operations Research, 69, 115–134. doi:10.1023/A:1018920709696
  • Gabrel, V., & Murat, C. (2003). Mathematical programming for earth observation satellite mission planning. In: Ciriani TA, Fasano G, Gliozzi S, Tadei R, editors. Operations research in space and air. New York: Springer.
  • Gabrel, V., & Vanderpooten, D. (2002). Enumeration and interactive selection of efficient paths in a multiple criteria graph for scheduling an earth observing satellite. European Journal of Operational Research., 139(3), 533–542. doi:10.1016/S0377-2217(01)00188-6
  • Galceran, E., & Carreras, E. (2013). A survey on coverage path planning for robotics. Robotics and Autonomous Systems. 61(12), 1258–1276. doi:10.1016/j.robot.2013.09.004
  • Globus, A., Crawford, J., Lohn, J., & Morris, R. (2002). Scheduling earth observing fleets using evolutionary algorithms: Problem description and approach. Proceeding of the third international NASA workshop on planning and scheduling for space.
  • Globus, A., Crawford, J., Lohn, J., & Pryor, A. (2003). A comparison of techniques for scheduling fleets of earth-observing satellites. Journal of the Operational Research Society, 56(8), 962–968.
  • Habet, D. (2009). Tabu search to solve real-life combinatorial optimization problems: A case of study. In: Abraham A, Hassanien AE, Carvalho AP, editors. Foundations of computational intelligence (pp. 129–151). New York: Springer.
  • Habet, D., & Vasquez, M. (2004). Solving the selecting and scheduling satellite photographs problem with a consistent neighborhood heuristic. Proceeding of the sixteenth IEEE international conference on tools with artificial intelligence (ICTAI’04).
  • Habet, D., Vasquez, M., & Vimont, Y. (2010). Bounding the optimum for the problem of scheduling the photographs of an agile earth observing satellite. Computational Optimization and Applications, 47(2), 307–333. doi:10.1007/s10589-008-9220-7
  • Hall, N. G., & Magazine, M. J. (1994). Maximizing the value of a space mission. European Journal of Operational Research, 78(2), 224–241. doi:10.1016/0377-2217(94)90385-9
  • Lemaître, M., Verfaillie, G., Jouhaud, F., Lachiver, J. M., & Bataille, N. (2000). How to manage the new generation of agile earth observation satellites. Proceeding of the international symposium on artificial intelligence, robotics and automation in space (ISAIRAS’00).
  • Lemaître, M., Verfaillie, G., Jouhaud, F., Lachiver, J. M., & Bataille, N. (2002). Selecting and scheduling observations of agile satellites. Aerospace Science and Technology, 6, 367–381. doi:10.1016/S1270-9638(02)01173-2
  • Li, Y., Wang, R., & Xu, M. (2014). Rescheduling of observing spacecraft using fuzzy neural network and ant colony algorithm. Chinese Journal of Aeronautics, 27, 678–687. doi:10.1016/j.cja.
  • Li, Y., Xu, M., & Wang, R. (2007). Scheduling observations of agile satellites with combined genetic algorithm. Proceedings of the 3rd international conference on natural computation (ICNC 2007): Vol. 3, pp. 29–33, Haikou, China.
  • Liao, D., & Tang, Y. (2005). Satellite imaging order scheduling with stochastic weather condition forecast. Proceeding of the IEEE international conference on systems, man and cybernetics, Vol. 3, pp. 2524–2529.
  • Liao, D.-Y., & Yang, Y.-T. (2007). Imaging order scheduling of an earth observation satellite. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 37(5), 794–802. doi:10.1109/TSMCC.2007.900668
  • Lin, W., & Chang, S. (2005). Hybrid algorithms for satellite imaging scheduling. Proceeding of the IEEE international conference on systems, man and cybernetics, Vol. 3, pp. 2518–2523.
  • Lin, W., & Liao, D. (2004). A tabu search algorithm for satellite imaging scheduling. Proceeding of the IEEE international conference on systems, man and cybernetics, Vol. 2, pp. 1601–1606.
  • Lin, W., Liao, D., Liu, C., & Lee, Y. (2005). Daily Imaging Scheduling of an Earth Observation Satellite. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 35(2), 213–223. doi:10.1109/TSMCA.2005.843380
  • Lin, W., Liu, C., Liao, D., & Lee, Y. (2003). Daily imaging scheduling of an earth observation satellite. Proceeding of the IEEE international conference on systems, man and cybernetics, Vol. 2, pp. 1886–1891.
  • Luo, K., Wang, H., Li, Y., & Li, Q. (2017). High-performance technique for satellite range scheduling. Computers & Operations Research, 85, 12–21. doi:10.1016/j.cor.2017.03.012
  • Maillard, A., Verfaillie, G., Pralet, C., Jaubert, J., & Lhermitte, J. (2016). Adaptable data download schedules for agile earth-observing satellites. Journal of Aerospace Computing, Information and Communication, 13 (8), 280–300.
  • Mansour, M. A. A., & Dessouky, M. M. (2010). A genetic algorithm approach for solving the daily photograph selection problem of the SPOT5 satellite. Computers & Industrial Engineering, 58(3), 509–520. doi:10.1016/j.cie.2009.11.012
  • Marinelli, F., Nocella, S., Rossi, F., & Smriglio, S. (2011). A Lagrangian heuristic for satellite range scheduling with resource constraints. Computers & Operations Research, 38(11), 1572–1583. doi:10.1016/j.cor.2011.01.016
  • Nelson, F. (2012). Scheduling optimization for imagery satellite constellations using column generation, PhD Thesis, George Mason University, Department of Systems Engineering and Operations Research, Volgenau School of Engineering.
  • Niu, X., Tang, H., & Wu, L. (2018). Multi-satellite observation scheduling for large area disaster emergency response. ISPRS—International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 1327–1331. doi:10.5194/isprs-archives-XLII-3-1327-2018
  • Niu, X., Tang, H., Wu, L., Deng, R., & Zhai, X. (2015). Imaging-duration embedded dynamic scheduling of earth observation satellites for emergent events. Mathematical Problems in Engineering, 2015, 1. doi:10.1155/2015/731734
  • Osman, I. H. (1993). Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Annals of Operations Research, 41(4), 421–451. doi:10.1007/BF02023004
  • Pinto, M., Barros, A., Noomen, R., Gelder, P., & Tessensohn, T. (2018). A new model proposal for integrated satellite constellation scheduling within a planning horizon given operational constraints. Proceedings of the 7th International Conference on Operations Research and Enterprise Systems, pp. 312–319.
  • Qiu, D., He, C., Liu, J., & Ma, M. (2013). A dynamic scheduling method of earth-observing satellites by employing rolling horizon strategy. The Scientific World Journal, doi:10.1155/2013/304047
  • Sarkheyli, A., Vaghei, B. G., & Bagheri, A. (2010). New tabu search heuristic in scheduling earth observation satellites. Proceeding of the second international conference on software technology and engineering (ICSTE’10).
  • Shaw, P. (1998). Using constraint programming and local search methods to solve vehicle routing problems. In M. Maher and J.-F. Puget (Eds.) Principles and practice of constraint programming, lecture notes in computer science (pp. 417–431). New York: Springer-Verlag.
  • Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2), 254–265. doi:10.1287/opre.35.2.254
  • Soma, P., Venkateswarlu, S., Santhalakshmi, S., Bagchi, T., & Kumar, S. (2004). Multi-satellite scheduling using genetic algorithms. Proceeding of the eighth international conference on space operations (SpaceOps’04).
  • Song, Y., Huang, D., Zhou, Z., & Chen, Y. (2018). An emergency task autonomous planning method of agile imaging satellite. Journal of Image and Video Processing, 2018, 2–11. doi:10.1186/s13640-018-0268-8
  • Spangelo, S., Cutler, J., Gilson, K., & Cohn, A. (2015). Optimization-based scheduling for the single-satellite, multi-ground station communication problem. Computers & Operations Research, 57, 1–16. doi:10.1016/j.cor.2014.11.004
  • Tangpattanakul, P., Jozefowiez, N., & Lopez, P. (2012). Multi-objective optimization for selecting and scheduling observations. In C.A. Coello, V. Cutello, K. Deb, S. Forrest, G. Nicosia, & M. Pavone (Eds.) Lecture notes in computer science. New York: Springer.
  • Toth, P., & Vigo, D. (2014). Vehicle routing: Problems, methods, and applications (2nd ed.). Philadelphia, PA: Society for Industrial and Applied Mathematics.
  • Vasquez, M., & Hao, J. (2001). A logic-constrained knapsack formulation and a tabu algorithm for the daily photograph scheduling of an earth observation satellite. Computational Optimization and Applications, 20(2), 137–157. doi:10.1023/A:1011203002719
  • Vasquez, M., & Hao, J. (2003). Upper bounds for the SPOT 5 daily photograph scheduling problem. Journal of Combinatorial Optimization, 7(1), 87–103. doi:10.1023/A:1021950608048
  • Vazquez, A. J., & Erwin, R. S. (2015). An introduction to optimal satellite range scheduling. New York: Springer.
  • Verfaillie, G. (2013). Planning and scheduling activities for earth surveillance and observation satellites: A constraint-based perspective, ICAPS 2013 Summer School, Perugia, Italy.
  • Verfaillie, G., & Lemaître, M. (2006). Tutorial on Planning Activities for Earth Watching and Observation satellites and Constellations: from Off-line Ground Planning to On-line On-board Planning, ICAPS 2006, The English Lake District, Cumbria, UK (http://icaps06.icaps-conference.org/).
  • Verfaillie, G., Lemaître, M., & Schiex, T. (1996). Russian doll search for solving constraint optimization problems. Proceeding of the thirteenth national conference on Artificial intelligence (AAAI’96); pp. 181–187.
  • Verfaillie, G., & Schiex, T. (1994). Solution reuse in dynamic constraint satisfaction problems. Proceeding of the twelfth national conference on artificial intelligence (AAAI’94), pp. 307–312.
  • Wall, M. (1995). GAlib - A C++ Genetic Algorithms Library, Version 2.4, MIT, Boston.
  • Wang, H., Xu, M., Wang, R., & Li, Y. (2009). Scheduling earth observing satellites with hybrid ant colony optimization algorithm. Proceeding of the international conference on artificial intelligence and computational intelligence (AICI’09).
  • Wang, J., Demeulemeester, E., Dishan, Q., & Liu, J. (2015a). Exact and Inexact Scheduling Algorithms for Multiple Earth Observation Satellites Under Uncertainties of Clouds. SSRN: https://ssrn.com/abstract=2634934 or doi:10.2139/ssrn.2634934.
  • Wang, J., Demeulemeester, E., & Qiu, D. (2014). A pure proactive scheduling algorithm for multiple earth observation satellites under uncertainties of clouds. Computers & Operations Research, 74, 1–13. doi:10.1016/j.cor.2016.04.014
  • Wang, J., Jing, N., Li, J., & Chen, Z. H. (2007). A multi-objective imaging scheduling approach for earth observing satellites. Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (GECCO ’07), pp. 2211–2218, London, UK.
  • Wang, J., Zhu, X., Yang, T., Zhu, J., & Ma, M. (2015b). Towards dynamic real-time scheduling for multiple earth observation satellites. Journal of Computer and System Sciences, 81(1), 110–124. doi:10.1016/j.jcss.2014.06.016
  • Wang, Y., Sheng, M., Zhuang, S., Zhang, S., Zhang, N., Liu, R., & Li, J. (2018). Multi-resource coordinate scheduling for earth observation. IEEE Journal on Selected Areas in Communications, 36 (2), 268–279.
  • Wolfe, J., & Stephen, S. E. (2000). Three scheduling algorithms applied to the earth observing systems domain. Management Science, 46(1), 148–168. doi:10.1287/mnsc.46.1.148.15134
  • Wu, G., Liu, J., Ma, M., & Dishan, Q. (2013). A two-phase scheduling method with the consideration of task clustering for earth observing satellites. Computers and Operations Research, 40(7), 1884–1894. doi:10.1016/j.cor.2013.02.009
  • Zhai, X., Niu, X., Tang, H., Wu, L., & Shen, Y. (2015). Robust satellite scheduling approach for dynamic emergency tasks. Mathematical Problems in Engineering, 2015, 1. doi:10.1155/2015/482923
  • Zufferey, N., Amstutz, P., & Giaccari, P. (2008). Graph colouring approaches for a satellite range scheduling problem. Journal of Scheduling, 11(4), 263–277. doi:10.1007/s10951-008-0066-8

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.