Journal of Global Optimization
An adaptive pursuit strategy for allocating operator probabilities
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Adaptive strategy selection in differential evolution
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Enhanced Differential Evolution With Adaptive Strategies for Numerical Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In order to automatically select the most suitable strategy for a specific problem without any prior knowledge, in this paper, we present an adaptive parameter selection technique for strategy adaptation in differential evolution (DE). First, a simple strategy adaptation mechanism is employed to implement the adaptive strategy selection in DE. Then, the probability- matching-based adaptive parameter selection method is proposed to select the best parameter of the strategy adaptation mechanism; in this way, it can accelerate the strategy adaptation mechanism to choose the most suitable strategy while solving a problem. Experimental results indicate that our method obtains better results in terms of the quality of the final solutions and the convergence speed, compared with the classical DE algorithms with single strategy.