The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.

In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

The transportation model is a well-recognized and applied algorithm in the distribution of products of logistics operations in enterprises. Multiple forms of solution are algorithmic and technological, which are applied to determine the optimal allocation of one type of product. In this research, the general formulation of the transport model by means of linear programming, where the optimal solution is integrated for different types of related products, and through a digital, dynamic, easy illustration Develops understanding of the Computer in Excel QM program. When choosing, the implementation of the form in the organization is provided.

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa

The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola