Champasak, PakinPanagant, NateePholdee, NantiwatBureerat, Sujin2022-11-232022-11-232020-05Champasak, P. vd. (2020). "Self-adaptive many-objective meta-heuristic based on decomposition for many-objective conceptual design of a fixed wing unmanned aerial vehicle". Aerospace Science and Technology, 100.1270-9638https://doi.org/10.1016/j.ast.2020.105783https://www.sciencedirect.com/science/article/pii/S1270963819316918http://hdl.handle.net/11452/29542Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for further decision making. In this paper, a many-objective optimisation problem for an unmanned aerial vehicle (UAV) is posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints. Aerodynamic analysis is carried out using a vortex lattice method, while aircraft component weights are estimated empirically. A new self-adaptive meta-heuristic based on decomposition is specifically developed for this design problem. The new algorithm along with nine established and recently developed multi-objective and many-objective meta-heuristics are employed to solve the problem, while comparative performance is made based upon a hypervolume indicator. The results reveal that the proposed optimiser is the best performer for this design task.eninfo:eu-repo/semantics/closedAccessAircraft conceptual designMany-objective optimisationAircraft performanceDynamic stabilityMultiobjective Evolutionary algorithmAerodynamic shape optimizationUnmanned aerial vehiclesSystemAircraft conceptual designAircraft performanceDynamic stabilityMany-objective optimisationAerodynamicsAntennasConceptual designDecision makingEconomic and social effectsFixed wingsHeuristic algorithmsOptimizationStabilityAircraft conceptual designsAircraft performanceComparative performanceHypervolume indicatorsObjective optimisationStability constraintsTake off gross weightVortex lattice methodVehicle performanceArticle0005258594000322-s2.0-85080082565100EngineeringAerospaceDecomposition; Evolutionary Multiobjective Optimization; Pareto Front