The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the sample average as an estimate of the true objective value. The number of samples is typically chosen arbitrarily and remains constant for the entire optimization process. This paper studies an adaptive sampling technique that varie...

There are many numerous methods for solving large-scale problems in which some of them are very flexible and efficient in both linear and non-linear cases. League championship algorithm is such algorithm which may be used in the mentioned problems. In the current paper, a new play-off approach will be adapted on league championship algorithm for solving large-scale problems. The proposed algori...

analysis of non-laminar flows in coarse alluvial beds has a wide range of applications in various civil engineering, oil and gas, and geology problems. darcy equation is not valid to analyze transient and turbulent flows, so non-linear equations should be applied. non-linear equations are classified into power and binomial equations. binomial equation is more accurate in a wide range of velocit...

Minimally nonideal matrices are a key to understanding when the set covering problem can be solved using linear programming. The complete classification of minimally nonideal matrices is an open problem. One of the most important results on these matrices comes from a theorem of Lehman, which gives a property of the core of a minimally nonideal matrix. Cornuéjols and Novick gave a conjecture on...

This paper proposes a new algorithm to remove Gaussian noise. The new method introduces two filters. The first one is linear filter that modifies the noisy and noisy-free pixels uniformly and regardless of the pixel location. The second one is non-linear filter, a direction-based filter used to re-estimate the first output, particularly the values of the edge pixels. Simulation results indicate...

The regularized least squares methods for the solution of ill-posed inverse problems are summarized, and appropriate references are stated. Additionally, an adap-tive multi-scale algorithm is proposed to solve highly ill-posed inverse problems with fewer degrees of freedom and comparable performance. The algorithm controls the level of detail in the reconstruction by distributing the ¯ne scale ...

To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. Its complexity is generally exponential in n. Noisy-OR reduces the complexity to linear, but can only represent reinforcing causal interactions. The non-impeding noisy-AND (NIN-AND) tree is the first causal model that explicitly expresses reinforcemen...