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The approaches for the parametric synthesis of the automatic control system (ACS) using the genetic algorithm that performs an approximation of Pareto-optimal solutions set are suggested. As a result, two approaches to multi-criteria optimization of ACS were considered: (1) the optimization problem was considered to be three-criteria for equally important criteria, (2) the optimization problem was...
In recent years, with the high frequency of the infectious diseases outbreak, the prediction of the infectious diseases has become more and more important, so effective prediction of the infectious diseases can safeguard social stability and promote national economic prosperity. In order to improve the predictive accuracy of infectious diseases, the weight and threshold of BP neural network was optimized...
In this paper, a problem of specifying HIV-infection parameters and immune response using additional measurements of the concentrations of the T-lymphocytes, the free virus, and the immune effectors at fixed times for a mathematical model of HIV dynamics is investigated numerically. The problem of specifying the parameters of the mathematical model (an inverse problem) is reduced to a problem of minimizing...
Integration of DGs in utility networks has increased significantly over the past years primarily as a result of growing energy demand, coupled with the environmental impacts posed by conventional fossil fuel-based generation. Improper planning of grid integration of intermittent DGs such as wind and solar PV may however pose negative impacts on the quality of power supplied by utility networks. This...
The paper presents the problem of parametric identification of induction motor mathematical model with the use of genetic algorithm (GA). The influence of population replacement strategy on the identification results is analyzed. The identified parameters of the model were determined as a result of minimization of performance index defined as the mean-square error of stator current and angular velocity...
To ensure the quality of traditional Chinese medicine is a key task for manufacturers of traditional Chinese medicine. In this paper, a novel method based on an improved trend balanced genetic algorithm is used for blending optimization in order to ensure the quality of traditional Chinese medicine. Our newly designed genetic algorithm is composed of 4 operators including a trend crossover operator,...
In this paper, unrelated parallel machine scheduling problem with job rejection and earliness-tardiness penalties is investigated. The objective is to minimize the total penalty cost by deciding job acceptance, assigning jobs on unrelated machines, and determining the processing sequence of jobs on each machine. To solve this problem, a mixed integer programming (MIP) model is established, and a hybrid...
The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms...
In this paper, we propose a hybrid genetic algorithm to solve assembly line balancing problem type E. There are two objectives to be achieved: Maximizing line efficiency balancing the workstation simultaneously. The model provide more realistic situation of assembly line balancing problem with station restriction and zoning constraints. The genetic algorithm may lack the capability of exploring the...
Physical Unclonable Function (PUF) is a new hardware security primitive that exploits the manufacturing variations of integrated circuits. Traditional arbiter PUF is vulnerable to machine learning based modeling attacks due to its linearity. Current mirror PUF uses non-linear current mirror to bring non-linearity into the challenge-response relationship and is claimed resistant to modeling attacks...
Model order reduction has been one of the most challenging topics in the past years. Conventional mathematical methods have been used to obtain a reduced order model of high order complex models. In this paper, genetic algorithm (GA) which is one of the artificial intelligence algorithms is used to approximate high-order transfer functions (TFs) as lower-order TFs. Genetic algorithm is considered...
The ball and beam system is a widely used tool for learning classical as well as advanced control techniques. The system with highly non linear characteristics is an excellent tool to represent unstable systems. The paper presents an optimal control strategy for controlling the position of ball on the beam. The system is an open loop unstable system. The control problem is a challenging one as the...
In this paper a prototype of crude network tanks system is modeled from the first principle, the system is then controlled using the PID (Proportional Integral Derivative) control system, the PID tuning parameters are optimized successfully using Genetic algorithm based on control performance indices (i.e. Mean Square Error (MSE), integral square error (ISE), integral absolute error (IAE), and integrated...
Road traffic congestion has aroused earnest concern in the public and the academic. Two apparent features of congested traffic networks are stochasticity and time dependency. In fact, different types of travelers have different route choice preferences, regarding to not only timeliness but also expense, which may involve multiple conflicting criteria. In this paper, a stochastic time-dependent network...
In today's world Wireless Sensor Networks (WSNs) has gained a lot of recognition because of its wide-ranging areas of applications. Sensor nodes in WSNare connected to each other by networks, mainly powered by a battery source. These sensor nodes have lesser amount of power and computational capabilities. Typically, sensor nodes are deployed in remote areas where replacement of their batteries once...
Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical...
The aircrew rostering problem belongs to the class of NP-Hard combinatorial optimization problems. It consists on constructing individual rosters through the distribution of planned pairings among available crew members in airline industries. In that purpose, several approaches were proposed through adapting imposed constraints to both the requirements and the internal regulations of each airline...
In this paper, an optimal adaptive controller using Genetic Algorithm for a ball and hoop system is proposed. It is difficult to design an optimal PID controller for a ball and hoop system because of its continuously varying parameters. The proposed scheme employs a PID controller with an ability to adjust its parameters when the dynamic behavior of the system changes, thus maintaining the optimality...
The majority of states/provinces now have renewable portfolio standards, with many requiring that over 20 percent of electricity sales be generated by renewable energy sources within the next five to fifteen years. A combination of public policy, incentives and economics is driving a rapid growth of distributed generation in the electric power system. The majority of these requirements will be addressed...
The computational power of nature is a mystery, although we have many computational models, but natural phenomena presents various challenges for them every day. NP-Complete and NP-Hard problems demand efficient solutions, but none of these problems are known to have a polynomial time solution. Nature inspired algorithms are playing major role in solving those problems with amazing efficiency. In...
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