Multiobjective Interior Optimization Computational Methods for Electronics BCS Superconductivity
Francisco Casesnoves
Abstract
Interior Optimization (IO) software and algorithms-programming were primarily presented in previous articles [3,4]. The mathematical framework of this new method, [Casesnoves, 2018-2020], was also proven [3,4]. The links among Interior Optimization, Graphical Optimization [Casesnoves, 2016-7], and classical methods in Nonlinear Equations Systems were developed. This paper is focused on software engineering with mathematical methods implementation in Multiobjective Interior Optimization programming as a primary subject. Second subject is Electronics applications of software in the field of BCS Superconductivity. These applications not only constitute a proof of the method, but also an useful BCS electronics numerical framework. They comprise a series of new BCS Equation optimization for multiple Type I superconductors, based on previous research for other different Type I ones previously published [3,4]. A Dual Optimization for two superconductors is also simulated. Several deductions/findings in computational technique for Multiobjective IO are guessed. Results are acceptable with low errors and 3D imaging demonstrations of the Interior Optimization utility.