Path-following interior-point algorithm for monotone linear complementarity problems

This paper presents a path-following full-Newton step interior-point algorithm for solving monotone linear complementarity problems. Under new choices of the defaults of the updating barrier parameter [Formula: see text] and the threshold [Formula: see text] which defines the size of the neighborhood of the central-path, we show that the short-step algorithm has the best-known polynomial complexity, namely, [Formula: see text]. Finally, some numerical results are reported to show the efficiency of our algorithm.

Accurate Insulating Oil Breakdown Voltage Model Associated with Different Barrier Effects

In modern power systems, power transformers are considered vital components that can ensure the grid’s continuous operation. In this regard, studying the breakdown in the transformer becomes necessary, especially its insulating system. Hence, in this study, Box–Behnken design (BBD) was used to introduce a prediction model of the breakdown voltage (VBD) for the transformer insulating oil in the presence of different barrier effects for point/plane gap arrangement with alternating current (AC) voltage. Interestingly, the BBD reduces the required number of experiments and their costs to examine the barrier parameter effect on the existing insulating oil VBD. The investigated variables were the barrier location in the gap space (a/d)%, the relative permittivity of the barrier materials (εr), the hole radius in the barrier (hr), the barrier thickness (th), and the barrier inclined angle (θ). Then, only 46 experiment runs are required to build the BBD model for the five barrier variables. The BBD prediction model was verified based on the statistical study and some other experiment runs. Results explained the influence of the inclined angle of the barrier and its thickness on the VBD. The obtained results indicated that the designed BBD model provides less than a 5% residual percentage between the measured and predicted VBD. The findings illustrated the high accuracy and robustness of the proposed insulating oil breakdown voltage predictive model linked with diverse barrier effects.

New complexity analysis of full Nesterov-Todd step infeasible interior point method for second-order cone optimization

We present a full Nesterov-Todd (NT) step infeasible interior-point algorithm for second-order cone optimization based on a different way to calculate feasibility direction. In each iteration of the algorithm we use the largest possible barrier parameter value ?. Moreover, each main iteration of the algorithm consists of a feasibility step and a few centering steps. The feasibility step differs from the feasibility step of the other existing methods. We derive the complexity bound which coincides with the best known bound for infeasible interior point methods.

Implementation of New Fission Barrier Model in TALYS Code

This paper is aimed to calculate neutron induced fission cross section using TALYS nuclear reaction code by utilizing new fission barrier model parameter. The new fission barrier model is based on minimization method of action functional of deformed nucleus fission trajectory in configuration of space from ground state to the exit barrier. New fission barrier parameter that obtained from this new model will be fed into the TALYS code to calculate the fission cross section of Th-232 and U-238 through statistical method. The result shows a better agreement with ENDF data compared to that of ETFSI (Extended Thomas-Fermi and Strutinsky Integral) or Mamdouh model of fission barrier for energy between 2 and 10 MeV.

A HYBRID ADAPTIVE ALGORITHM FOR LINEAR OPTIMIZATION

Recently, using the framework of self-regularity, Salahi in his Ph.D. thesis proposed an adaptive single step algorithm which takes advantage of the current iterate information to find an appropriate barrier parameter rather than using a fixed fraction of the current duality gap. However, his algorithm might do at most one bad step after each good step in order to keep the iterate in a certain neighborhood of the central path. In this paper, using the same framework, we propose a hybrid adaptive algorithm. Depending on the position of the current iterate, our new algorithm uses either the classical Newton search direction or a self-regular search direction. The larger the distance from the central path, the larger the barrier degree of the self-regular search direction is. Unlike the classical approach, here we control the iterates by guaranteeing certain reduction of the proximity measure. This itself leads to a one dimensional equation which determines the target barrier parameter at each iteration. This allows us to have a large update algorithm without any need for safeguard or special steps. Finally, we prove that our hybrid adaptive algorithm has an [Formula: see text] worst case iteration complexity.