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Existing differential evolution (DE) algorithms often face two challenges. The first is that the optimization performance is significantly affected by the ad hoc configurations of operators and parameters for different problems. The second is the long runtime for real-world problems whose fitness evaluations are often expensive. Aiming at solving these two problems, this paper develops a novel double-layered...
Recently, partitional clustering approaches based on Evolutionary Algorithms (EAs) have shown promising in solving the data clustering problems. However, with the nearest prototype (NP) rule as the method for decoding, most of them are only suitable for clustering datasets with convex (e.g. hyperspherical) clusters. In this paper, we propose an automatic clustering approach using particle swarm optimization...
Nurse rostering is a non-deterministic polynomial problem with many constraints. In the literature, a number of heuristic approaches have been proposed, but few of them can achieve satisfying performance on both solution quality and search speed. Inspired by the successful experience of ant colony optimization (ACO) on many highly-constrained problems, this paper proposed an ant colony optimization...
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