Experiments with new stochastic global optimization search techniques
Computers and Operations Research
A Pattern Search Filter Method for Nonlinear Programming without Derivatives
SIAM Journal on Optimization
Journal of Global Optimization
Comparison of multi-modal optimization algorithms based on evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization
Journal of Global Optimization
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
A simulated annealing driven multi-start algorithm for bound constrained global optimization
Journal of Computational and Applied Mathematics
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
A derivative-free filter driven multistart technique for global optimization
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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Multilocal programming aims to locate all the local solutions of an optimization problem. A stochastic method based on a multistart strategy and a derivative-free filter local search for solving general constrained optimization problems is presented. The filter methodology is integrated into a coordinate search paradigm in order to generate a set of trial approximations that might be acceptable if they improve the constraint violation or the objective function value relative to the current one. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.