Albert A. Groenwold

Learn More
A number of recently proposed variants of the particle swarm optimization algorithm (PSOA) are applied to an extended Dixon-Szegö bound constrained test set in global optimization. Of the variants considered, it is shown that constriction as proposed by Clerc, and dynamic inertia and maximum velocity reduction as proposed by Fourie and Groenwold, represent(More)
Successful gradient-based sequential approximate optimization (SAO) algorithms in simulation-based optimization typically use convex separable approximations. Convex approximations may however not be very efficient if the true objective function and/or the constraints are concave. Using diagonal quadratic approximations, we show that non-convex(More)
1. Abstract We present an incomplete series expansion (ISE) as a basis for function approximation. The ISE is expressed in terms of an approximate Hessian matrix which may contain second, third and even higher order 'main' or diagonal terms, but which excludes 'interaction' or off-diagonal terms. From the ISE, a family of approximate interpolating functions(More)
We consider 'invariance' in the context of optimization algorithms. 'Scale invariance' implies algorithm performance that is independent of uniform scaling of all the design variables. 'Frame invariance' in turn implies algorithm performance that is independent of frame translation and rotation. The notion of scale and frame invariance is not new to the(More)