Discrete particle swarm optimization for constructing uniform design on irregular regions

Other advantages of our ProjPSO algorithm over current methods are (1) our experience is that the time required to generate the optimal design is gen- erally a lot faster than many

Shih-Cheng Horng , Feng-Yi Yang, “Embedding particle swarm in ordinal optimization to solve stochastic simulation optimization problems”, International Journal of Intelligent

Example: Image produced by a spherical mirror... 14.5 Spherical

The Liouville CFT on C g,n describes the UV region of the gauge theory, and the Seiberg-Witten (Gaiotto) curve C SW is obtained as a ramified double cover of C g,n ... ...

Part (d) shows the Gemini North telescope, which uses the design in (c) with an objective mirror 8 meters in diameter...

Large data: if solving linear systems is needed, use iterative (e.g., CG) instead of direct methods Feature correlation: methods working on some variables at a time (e.g.,

Spatially resolved, time-averaged, multipoint measurements of flame emission spectra using two Cassegrain mirrors and two spectro- meters are performed and the results are used

Moreover, this chapter also presents the basic of the Taguchi method, artificial neural network, genetic algorithm, particle swarm optimization, soft computing and