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Many objective optimization results form a set of solutions in four dimensional hyper objective space and for visualization it is represented on a two dimension objective space.
Many objective optimization results form a solution in a four dimensional hyper objective space and for visualization it is represented on a two dimension objective space.
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Bader et al. [24] first divided solutions in a population into a number of sets of the same size, and then transformed the problem into a single-objective optimization problem whose objective is hyper-volume.
In other words, complex social processes and events occurring in a school are reduced to figures, scores, targets or tables of data that may appear 'misleadingly objective and hyper-rational' (Ball 2003).
The new algorithms are based on the DIRECT scheme for global optimization combined with different algorithms for local optimization in hyper-boxes which contain interesting objective function values.
The essence of the crowing distance is to find the Euclidean distance between each individual in a front based on m objectives in m dimensional hyper space.
Auger et al. [30] incorporated preferences into an evolutionary many-objective optimization algorithm via weighted hyper-volume, and defined a preferred region of the objective space through a weighted function.
We begin by presenting a numerical investigation of the properties of the objective function f (x) in the search space hyper boxes where we perform local optimization.
Since the objective function is often not convex within the hyper-boxes where local optimization is applied, it is not a priori clear that the gradient-based schemes will be able to correctly locate the global minima.
An immersion objective with a high N.A. typically consists of a hyper-hemisphere followed by one or two aplanatic collectors and then two or more sets of doublets.
Hyper hemispheric lens belong to the ultra-wide field-of-view optical objectives.
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