Data mining: concepts and techniques
Data mining: concepts and techniques
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Faster convergence by means of fitness estimation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Journal of Global Optimization
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A robust stochastic genetic algorithm (StGA) for global numerical optimization
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
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A hybrid global optimization algorithm is developed in this research. The probability of finding the global optimal solution is increased by reducing the search space. The activities of classification, association, and clustering in data mining are employed to achieve this purpose. The hybrid algorithm developed uses data mining (DM), evolution strategy (ES) and sequential quadratic programming (SQP) to search for the global optimal solution. For unconstrained optimization problems, data mining techniques are used to determine a smaller search region that contains the global solution. For constrained optimization problems, the data mining techniques are used to find the approximate feasible region or the feasible region with better objective values. Numerical examples demonstrate that this hybrid algorithm can effectively find the global optimal solutions for two benchmark test problems.