Learning problems, such as logistic regression, are typically formulated as pure optimization problems defined on some loss function. We argue that this view ignores the fact that the loss function depends on stochastically generated data which in turn determines an intrinsic scale of precision for statistical estimation. By considering the statistical properties of the update variables used du...

The present study attempts to apply an efficient yet simple optimization (SOPT) algorithm to optimum design of truss structures under stress and displacement constraints. The computational efficiency of the technique is improved through avoiding unnecessary analyses during the course of optimization using the so-called upper bound strategy (UBS). The efficiency of the UBS integrated SOPT algori...

We introduce an unconstrained multicriteria optimization problem and discuss its relation to various well-known scalar robust optimization problems with a finite uncertainty set. Specifically, we show that a unique solution of a robust optimization problem is Pareto optimal for the unconstrained optimization problem. Furthermore, it is demonstrated that the set of weakly Pareto optimal solution...

In this paper, several new set quality metrics are introduced that can be used to evaluate the ‘‘goodness’’ of an observed Pareto solution set. These metrics, which are formulated in closed-form and geometrically illustrated, include hyperarea difference, Pareto spread, accuracy of an observed Pareto frontier, number of distinct choices and cluster. The metrics should enable a designer to eithe...

A number of authors made the claim that a multiobjective approach preserves genetic diversity better than a single objective approach. Sofar, none of these claims presented a thorough analysis to the effect of multiobjective approaches. In this paper, we provide such analysis and show that a multiobjective approach does preserve reproductive diversity. We make our case by comparing a pareto mul...

The multiobjective optimization of Slide-o-Cam is reported in this paper. Slide-o-Cam is a cam mechanism with multiple rollers mounted on a common translating follower. This transmission provides pure-rolling motion, thereby reducing the friction of rack-and-pinions and linear drives. A Pareto frontier is obtained by means of multiobjective optimization. This optimization is based on three obje...

in this article, modeling and optimization of power consumption of two–stage compressed airsystem has been investigated. to do so, the two – stage compressed air cycle with intercooler offajr petroleum company was considered. this cycle includes two centrifugal compressors, ashell, and a tube intercooler. for modeling of power consumption, actual compressors isentropicefficiencies and intercool...

in this paper, a consistent pattern with the optimal coordinated design of pss and sssc controller to improve the damping of low frequency oscillations is shown. in this design, sensing and signal transmission time delays are considered as effectiveness parameters. the design problem has been considered an optimization problem and biogeography-based optimization (bbo) algorithm is used for sear...

Energy and spectral efficiency are the main challenges in 5th generation of mobile cellular networks. In this paper, we propose an optimization algorithm to optimize energy by maximizing efficiency. Our simulation results show a significant increase terms as well whenever user is connected low power indoor base station. By applying proposed algorithm, network performance improvements up 9 bit/s...