Ricardo Sérgio Prado

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This chapter presents a general framework of Differential Evolution algorithm for combinatorial optimization problems. We define the differences between a given pair of solutions in the differential mutation as a set of elementary movements in the discrete search space. In this way, the search mechanism and self-adaptive behavior of the differential(More)
The Differential Evolution (DE) algorithm is an important and powerful evolutionary optimizer in the context of continuous numerical optimization. Recently, some authors have proposed adaptations of its differential mutation mechanism to deal with combinatorial optimization, in particular permutationbased integer combinatorial problems. In this paper, the(More)
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