Pages that link to "Item:Q1411321"

The following pages link to A note on the Griewank test function (Q1411321):

Displaying 21 items.

• Test problem generator for unconstrained global optimization (Q337165) (← links)
• Uncertainty assessment for inverse problems in high dimensional spaces using particle swarm optimization and model reduction techniques (Q410014) (← links)
• Real-coded genetic algorithm with uniform random local search (Q529960) (← links)
• An integral function and vector sequence method for unconstrained global optimization (Q540707) (← links)
• Self-adaptive randomized and rank-based differential evolution for multimodal problems (Q656961) (← links)
• A trust-region algorithm for global optimization (Q861513) (← links)
• Globally convergent evolution strategies for constrained optimization (Q887166) (← links)
• Basin hopping networks of continuous global optimization problems (Q1642814) (← links)
• The gradient evolution algorithm: a new metaheuristic (Q1749835) (← links)
• Optimizing radial basis functions by d.c. programming and its use in direct search for global derivative-free optimization (Q1935888) (← links)
• Stochastic optimization with adaptive restart: a framework for integrated local and global learning (Q2022223) (← links)
• A particle swarm pattern search method for bound constrained global optimization (Q2454725) (← links)
• Global optimization using a dynamical systems approach (Q2494313) (← links)
• A derivation of the number of minima of the Griewank function (Q2518647) (← links)
• Numerical studies of some generalized controlled random search algorithms (Q2911580) (← links)
• Comparison of deterministic and stochastic approaches to global optimization (Q3025042) (← links)
• A comparative study of some real-coded genetic algorithms for unconstrained global optimization (Q3096889) (← links)
• Handling of Constraints in Efficient Global Optimization (Q4987284) (← links)
• Escaping local minima with local derivative-free methods: a numerical investigation (Q5093686) (← links)
• Revisiting `survival of the fittest' principle in global stochastic optimisation: incorporating anisotropic mutations (Q6143064) (← links)
• A review of recent advances in surrogate models for uncertainty quantification of high-dimensional engineering applications (Q6663327) (← links)