P. Narayan, P. Meyer, and D. Campbell, “Embedding
human experting cognition into autonomous UAS trajectory planning,” IEEETransactions on Cybernetics, vol. 43, no. 2, pp. 530–543, 2013. DOI: 10.1109/TSMCB.2012.2211349
 A. Rucco, G. Notarstefano, and J. Hauser, “An efficient minimum time trajectory generation strategy for two-track car vehicles,” IEEE Transactions on Control Systems Technology, vol. 23, no. 4, pp. 1505– 1519, 2015. DOI: 10.1109/TCST.2014.2377777
 Z. Chen and H. T. Zhang, “A minimal control multiagent for collision avoidance and velocity alignment,” IEEE Transactions on Cybernetics, vol. 47, no. 8, pp. 2185–2192, 2017. DOI: 10.1109/TCYB.2017.2712641
 A. J. Hausler, A. Saccon, A. P. Aguiar, J. Hauser, and A. M. Pascoal, “Energy-optimal motion planning for multiple robotic vehicles with
collision avoidance,” IEEE Transactions on Control Systems Technology, vol. 24, no. 3, pp. 867–883, 2016. DOI: 10.1109/TCST.2015.2475399
 L. Paull, C. Thibault, A. Nagaty, M. Seto, and H. Li, “Sensor-driven area coverage for an autonomous fixed-wing unmanned aerial vehicle,”IEEE Transactions on Cybernetics, vol. 44, no. 9, pp. 1605–1618, 2014. DOI: 10.1109/TCYB.2013.2290975
 H. Peng, B. Chen, and Z. Wu, “Multi-objective transfer to librationpoint orbits via the mixed low-thrust and invariant-manifold approach,”Nonlinear Dynamics, vol. 77, no. 1, pp. 321–338, 2014. https://doi.org/10.1007/s11071-014-1296-2
 H. Peng and W. Wang, “Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points,” Advances in Space Research, vol. 58, no. 7, pp. 1331–1347, 2016. DOI: 10.1016/j.asr.2016.06.023
 W. Wang and H. Peng, “A fast multi-objective optimization design method for emergency libration point orbits transfer between the sunearth and the earth-moon systems,” Aerospace Science and Technology,vol. 63, pp. 152–166, 2017. https://doi.org/10.1016/j.ast.2016.12.026
 C. Yang, Z. Li, and J. Li, “Trajectory planning and optimized adaptive control for a class of wheeled inverted pendulum vehicle models,”IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 24–36, 2013.
 J.J. Sellers, Returning from Space: Re-Entry. Understanding Space: An Introduction to Astronautics. 2000. Available online: https://www.faa.gov/sites/faa.gov/files/about/office_org
 M.Tava,; S. Suzuki, Multidisciplinary design optimization of the shape and trajectory of a reentry vehicle. Trans. Jpn. Soc. Aeronaut. Space Sci. 2002, 45, 10–19. https://doi.org/10.2322/tjsass.45.10
 M. Mor,; E. Livne, Integrated aeroelastic shape optimization of flight vehicles. In Proceedings of the 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Austin, TX, USA, 18–21 April 2005. Collection of Technical Papers.
 M. Nosratollahi,; M. Mortazavi,; A. Adami,; M. Hosseini, Multidisciplinary design optimization of a reentry vehicle using genetic algorithm. Aircr. Eng. Aerosp. Technol. 2010, 82, 194–203. https://doi.org/10.3390/applmech3040067
 M. Nosratollahi,; M. Hosseini,; A. Adami, Multidisciplinary Design Optimization of a Reentry Vehicle’s Configuration. In Proceedings of the 8th Aerospace International conference, Isfahan, Iran, 17–19 February 2009. ttps://doi.org/10.3390/applmech3040067
 A. Adami,; M. Hosseini,; M. Nosratollahi, Multiobjective Optimization of a Reentry Vehicle’s Aerodynamic Shape. In Proceedings of the 17th Mechanic International conference, Tehran, Iran, 19–21 May 2009. https://doi.org/10.3395/applmech3041267
 M. Nosratollahi,; M. Hosseini,; A. Adami, Multidisciplinary design optimization of a controllable reentry capsule for minimum landing velocity. In Proceedings of the 51st Collection of Technical Papers—AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Orlando, FL, USA, 12–15 April 2010. https://doi.org/10.2514/6.2010-3009
 A. Adami,; M. Nosratollahi,; M. Mortazavi,; M. Hosseini, Multidisciplinary design optimization of a manned reentry mission considering trajectory and aerodynamic configuration. In Proceedings of the 5th International Conference on Recent Advances in Space Technologies–RAST 2011, Istanbul, Turkey, 9–11 June 2011. DOI:10.1109/RAST.2011.5966908
 D. Dirkx,; E. Mooij, Conceptual Shape Optimization of Entry Vehicles: Applied to Capsules and Winged Fuselage Vehicles; Springer Aerospace Technology; Springer: Berlin/Heidelberg, Germany, 2017.
 Y. Wu,; J. Deng,; L. Li,; X. Su,; L. Lin, A hybrid particle swarm optimization-gauss pseudo method for reentry trajectory optimization of hypersonic vehicle with navigation information model. Aerosp. Sci. Technol. 2021. ttps://doi.org/10.1016/j.ast.2021.107046
 Hong Liu, “Multiobjective Evolutionary Computation for Noncircular Missile Shape Optimization”, 42nd AIAA Aerospace Sciences Meeting and Exhibit, paper 04-453, 2004.https://doi.org/10.2514/6.2004-453
 W. Su1, Y. Zuo and Z. Gao, “Preliminary Aerodynamic Shape Optimization Using Genetic Algorithm and Neural Network”, 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, paper 06-7106, 2006. https://doi.org/10.2514/6.2006-7106
 k. Cui and G.W. Yang, “Shape Optimization for Hypersonic Arc-Wing Missiles”, Journal of Spacecraft and Rockets, Vol. 47, No. 4, pp. 694–700, 2010. https://doi.org/10.2514/1.45882
 A. Z. Al-Garni, , A. H. Kassem, , and A. M. Abdallah, , “Aerodynamic-Shape Optimization of Supersonic-Missiles Using Monte Carlo”, International Review of Aerospace Engineering, Vol. 1, No. 1, 2008. DOI:10.2514/2.3615
 O. Tekinalp, , and M. Bingol, , “Simulated Annealing for Missile Optimization: Developing Method and Formulation Techniques”, Journal of Guidance, Control, and Dynamics, Vol. 27, No. 4, pp. 616–626, 2004. https://doi.org/10.2514/1.2103
 H . Nobahari, S. Y. Nabavi, S. H. Pourtakdoust, “Aerodynamic Shape Optimization of Unguided Projectiles Using Ant Colony Optimization and Genetic Algorithm”, 25th International Congress of the Aeronautical Sciences, ICAS Paper 2006-3.6S, Hamburg,2006. http://dx.doi.org/10.4314/jfas.v8i3s.385
 A. Ekrami Kivaj, A. Basohbat Novinzadeh, and F. Pazooki, “Spacecraft reentry trajectory optimization by heuristic optimization methods and optimal control theory,” Int. J. Dyn. Control., 2022. https://doi.org/10.1007/s40435-022-01033-0
 P. N. Desai, D. T. Lyons, J. Tooley, and J. Kangas, “Entry, descent, and landing
operations analysis for the Stardust entry capsule,” J. Spacecr. Rockets, vol. 45, no. 6, pp. 1262-1268, 2008.
 M. Ghoreyshi, D. Vallespin, A. Da Ronch, K. J. Badcock, J. Vos, and S. Hitzel,
“Complex System Optimization: A Review
of Analytical Target Cascading,
Collaborative Optimization, and Other
AIAA Atmospheric Flight Mechanics Conference, 2010.
 M. Ghoreyshi, K. J. Badcock, A. D. Ronch, S. Marques, A. Swift, and N.
Ames, “Framework for establishing limits of tabular aerodynamic models for flight
dynamics analysis,” J. Aircr., vol. 48, no. 1, pp. 42-55, 2011.
 J. T. Betts, and I. Kolmanovsky, “Practical Methods for Optimal Control using Nonlinear Programming,” Appl. Mech. Rev., vol. 55, B68, 2002. https://doi.org/10.1115/1.1483351
 P. Gurfil, and N. J. Kasdin, “Niching genetic algorithms-based characterization of geocentric orbits in the 3D elliptic restricted three-body problem”, Comput. Methods Appl. Mech. Eng., vol. 191, pp. 5683-5706, 2002. https://doi.org/10.1016/S0045-7825(02)00481-4
 A. Da Ronch, M. Ghoreyshi, D. Vallespin, K. J. Badcock, Z. Mengmeng,
J. Oppelstrup, and A. Rizzi, “A framework for constrained control allocation
using CFD-based tabular data,” At the 49th AIAA Aerospace Sciences Meeting,
AIAA–2011–925, Orlando, Florida, 2011.
 A. Rahimi, K. Dev Kumar, and H. Alighanbari, Particle swarm optimization applied to spacecraft re-entry trajectory. J. Guid Control Dyn., vol. 36, no. 1, pp. 307-310, 2012. https://doi.org/10.2514/1.56387
 H. Duan, and S. Li, “Artificial bee colony–based direct collocation for re-entry trajectory optimization of hypersonic vehicle,” IEEE Trans. Aerosp Electron Syst., vol. 51, no. 1, pp. 615–626, 2015. https://doi.org/10.1109/TAES.2014.120654
 K. Graichen, and N. Petit, Constructive Methods for Initialization and Handling Mixed State-Input Constraints in Optimal Control. J. Guid Control Dyn., vol. 31, no. 5, pp. 1334-1343, 2008. https://doi.org/10.2514/1.33870
 M. Samani, M. Tafreshi, I. Shafieenejad, and A. A. Nikkhah, “Minimum-time open-loop and closed-loop optimal guidance with GA-PSO and neural-fuzzy for Samarai MAV flight,” IEEE Aerosp Electron. Syst. Mag., vol. 30, pp. 28-37, 2015. https://doi.org/10.1109/MAES.2015.7119822
 W. Chen, M. Panahi, H. R. Pourghasemi, “Performance evaluation of GIS-based new ensemble data mining techniques of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) for landslide spatial modeling,” Catena, vol. 157, pp. 310-324, 2017. https://doi.org/10.1016/j.catena.2017.05.034
 H. K. Abdulkhader, J. Jacob, and A. T. Mathew, “Fractional-order lead-lag compensator-based multi-band power system stabilizer design using a hybrid dynamic GA-PSO algorithm,” IET Gener Transm. Distrib., vol. 12, pp. 3248-3260, 2018. https://doi.org/10.1049/iet-gtd.2017.1087
 Y. Liu, X. Li, P. Jiang, Zh. Du, Zh. Wu, B. Sun, and X. Huang, « Evolutionary multi-objective trajectory optimization for a redundant robot in Cartesian space considering obstacle avoidance,” Mech. Sci., vol. 13, pp. 41–53, 2022. https://doi.org/10.5194/ms-13-41-2022
 H. Yang, S. Li, and X. Bai, « Fast homotopy method for asteroid landing trajectory optimization using approximate initial costates,” J. Guid Control Dyn., vol. 42, no. 3, pp. 585-597, 2019. https://doi.org/10.2514/1.G003414
 H. Xu, W. Li, X. Wang, C. Hu, and S. Zhang, “Multidisciplinary reliability design optimization under time-varying uncertainties,” Adv. Mech. Eng., vol. 8, no. 11, pp. 1–11, 2016.
 L. Jaege, and T. Jorquera, “Uncertainty propagation in multi-agent systems for multidisciplinary optimization problems,” In: 10th World Congress on Structural and Multidisciplinary Optimization, Orlando, Florida, USA, May 19 - 24, 2013.
 J. Berends, and M. Van Tooren, “MDO Design Support by Integrated Engineering Services within a Multi-Agent Task Environment Framework,” In: The 26th Congress of ICAS and 8th AIAA ATIO, 2008. https://doi.org/10.2514/6.2008-8947
 I. Shafieenejad, A. B. Novinzadeh, V. R. Molazadeh, “Comparing and analyzing min-time and min-effort criteria for the free true anomaly of low-thrust orbital maneuvers with a new optimal control algorithm,” Aerosp Sci. Technol., vol. 4, no. 35, pp. 116-134, 2014. https://doi.org/10.1016/j.ast.2014.03.009
 H. Peng, C. Yang, Y. Li, S. Zhang, and B. Chen, “Surrogate-based parameter optimization and optimal control for the optimal trajectory of Halo orbit rendezvous,” Aerosp Sci. Technol., vol. 26, no. 1, pp. 176-184, 2013. https://doi.org/10.1016/j.ast.2012.04.001
 D. Karaboga, and B. Basturk, “On the performance of artificial bee colony (ABC) algorithm,” Appl. Soft Comput., vol. 8, no. 1, p. 687, 2008. http://dx.doi.org/10.1016/j.asoc.2007.05.007
 B. Akay, and D. Karaboga, “Artificial bee colony algorithm for large-scale problems and engineering design optimization,” J. Intell. Manuf., vol. 23, no. 4, pp. 1001-1014, 2012. https://doi.org/10.1007/s10845-010-0393-4
 M. Srinivas, and L. M. Patnaik, “Genetic algorithms: A Survey,” Computer, vol. 27, no. 6, pp. 17-26, 1994. https://doi.org/10.1109/2.294849
 H. S. Ramadan, A. Fathy, and M. Becherif, “Optimal gain scheduling of VSC-HVDC system sliding mode control via artificial bee colony and mine blast algorithms,” IET Gener. Transm. Distrib., vol. 12, no. 3, p. 661, 2017. https://doi.org/10.1049/iet-gtd.2017.0935
 Sh. Zhang, “An Optimal Design Scheme of Missile Trajectory,” In: Journal of Physics: Conference Series, 2022 International Conference on Automation and Space Science & Technology, 2022. doi:10.1088/1742-6596/2220/1/012012
 C. R. Hargraves, and S. W. Paris, « Direct trajectory optimization using non-linear programming and collocation,” J. Guid Control Dyn., vol. 10, no. 4, pp. 338-342, 1987.