ACM Transactions on Mathematical Software (TOMS)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Lipschitz and Hölder global optimization using space-filling curves
Applied Numerical Mathematics
Very fast simulated re-annealing
Mathematical and Computer Modelling: An International Journal
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This paper proposes a new multi-start, stochastic global optimization algorithm that uses dimensional reduction techniques based upon approximations of space-filling curves, simulated annealing and particle swarm optimization, aiming at finding global minima of real-valued functions that are not necessarily well behaved, that is, are not required to be differentiable, continuous, or even satisfying Lipschitz conditions. The overall idea is as follows: given a real-valued function F with a multidimensional and compact domain D, the method builds an equivalent one-dimensional problem by composing F with a linearization of D, searches for a small population of candidates and returns to the original high-dimensional domain, this time with a small set of promising starting points.