A Performance Comparison of Chaotic Simulated Annealing Models for Solving the N-queen Problem
Chaotic neural network models employing two chaotic simulated annealing (CSA) schemes, one with decaying self-couplings and the other with a decaying time-step, are used to solve the N-queen problem. Their optimisation performances are compared in terms of feasibility, efficiency, robustness and scalability in a two-parameter domain chosen for each model. Computational results show that the decaying self-coupling approach offers better feasibility, robustness and scalability, with efficiency being comparable for the two models. Correlation between feasibility and efficiency illustrates some chaotic search characteristics common to both models.
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