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The Differential Evolution (DE) is a powerful bio-inspired algorithm searching optimal solutions. The actual DE modifications can handle the real, integer and discrete valued problems. The values of the discrete-valued variables represent the integer indices addressing the discrete samples in the ordered array. The optimization in unordered samples leads to a random search. This paper proposes a novel modification dealing with d-dimensional discrete vertices. A vertex hashing is used to strengthen the local properties of a dataset and to improve the spatial convergence of the evolution.
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