The biologically inspired concept of hidden genes has been recently introduced in genetic algorithms to solve optimization\r\nproblems where the number of design variables is variable. In multigravity-assist trajectories, the hidden genes genetic algorithms\r\ndemonstrated success in searching for the optimal number of swing-bys and the optimal number of deep space maneuvers. Previous\r\ninvestigations in the literature for multigravity-assist trajectory planning problems show that the standard differential evolution is\r\nmore effective than the standard genetic algorithms. This paper extends the concept of hidden genes to differential evolution. The\r\nhidden genes differential evolution is implemented in optimizingmultigravity-assist space trajectories. Case studies are conducted,\r\nand comparisons to the hidden genes genetic algorithms are presented in this paper.
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