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This paper demonstrates design of a commercial aircraft at the conceptual design stage by considering 2 objective functions i.e. minimization of aircraft maximum takeoff weight and maximization of lift-to-drag ratio multi-objective evolutionary algorithms (MOEAs). Dynamic stability is taken as a design constraint while design variables include geometrical properties of the plane, consisting of the wing, empennage and fuselage. The aerodynamic coefficients of flight were calculated by using SUAVE (Aerospace Conceptual Design Environment) whereas dynamic stability analysis was achieved through using Athena vortex lattice (AVL) software. Pareto front obtained from various MOEAs are compared by Hypervolume. MOEAs are contained as MOEA / D, Two-Arch2, RPBILDE, PICEA-g, KnEA/A-ENS and KnEA. The obtained solutions for aircraft can be used for further design in the preliminary design stage. [ABSTRACT FROM AUTHOR]

Plagiarism is deemed a serious ethical offense. Without proper protection and accurate detection algorithms, the number of innovations would significantly dwindle, impeding the advancement of national research and education. Especially in programming courses, plagiarism is extremely common. Most students tend to do their homework in the simplest way: copying the source code of others. Such unpleasant issues must be addressed to preclude this misbehavior before it becomes students’ habit, and to promote positive attitudes in our juveniles. In this paper, we, propose an algorithm to identify original source codes, helping instructors to pinpoint whom to monitor and be able to set measures or correctly warn each wrong-doing student. This work introduces a rule, derived from a m+l evolutionary algorithm, for identifying which source codes are original. First, we run the maximum spanning tree algorithm to generate a phylogenetic tree, representing the relationships and sequences of plagiarisms. Then, we apply our proposed rule to identify the source and its copies, whose relations are represented by arrows’ directions. The experiment result shows that the proposed rule yields the accuracy of 90.24%. [ABSTRACT FROM AUTHOR]