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This paper proposes a novel adaptive local search algorithm for tackling real-valued (or continuous) dynamic optimization problems. The proposed algorithm is a simple single-solution based metaheuristic that perturbs the variables separately to select the search direction for the following step and adapts its step size to the gradient. The search directions that appear to be the most promising are...
This paper proposes a novel implementation of micro-Differential Evolution (μDE) that incorporates within the DE scheme an extra search move that attempts to improve the best solution by perturbing it along the axes. These extra moves complement the DE search logic and allows the exploration of the decision space from an alternative perspective. In addition, these extra moves at subsequent activations...
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