The article deals with the modeling and synthesis of Gaussian filters designed for selection of complex noise-like signals in the path of a hydroacoustic receiving station. The formulation and solution of the problem ...
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In this study, a multiobjective model was devoted to the objectives of minimizing blood supply chain costs and minimizing the waiting time of blood donors for blood transfusion and minimizing blood transfusion schedul...
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In this study, a multiobjective model was devoted to the objectives of minimizing blood supply chain costs and minimizing the waiting time of blood donors for blood transfusion and minimizing blood transfusion schedule and increasing the efficiency of fixed and mobile centers in collecting blood. One of the most important constraints considered in the mathematical model is the capacity constraints of considering fixed and mobile blood facilities and management of the transfer of blood products to centers for collecting and distinguishing healthy and unhealthy blood. A multiobjective model was considered with the objectives of minimizing blood supply chain costs, the waiting time of blood donors for blood transfusion, and blood transfusion timing and increasing the efficiency of fixed and mobile centers in blood collection. The model findings were analyzed in order to validate the model on a larger scale, using the meta-innovative algorithm NSGAII and MOSPO. According to the research findings, we suggest that fuzzy uncertainty and fair distribution problem shouldn’t be added to the dimensions of the main problem, and further analysis should be done in this area. It was shown that the NSGAII algorithm’s performance was better than the MOPSO meta-heuristic algorithm.
Acceptance sampling plan, a practical technique in the field of quality control in industrial production, employs a small number of samples to determine whether the product meets quality standards. The Skip-lot sampli...
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This article is concerned with the problem of minimizing a smooth function over the Stiefel manifold. In order to address this problem, we introduce two adaptive scaled gradient projection methods that incorporate sca...
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This article is concerned with the problem of minimizing a smooth function over the Stiefel manifold. In order to address this problem, we introduce two adaptive scaled gradient projection methods that incorporate scaling matrices that depend on the step-size and a parameter that controls the search direction. These iterative algorithms use a projection operator based on the QR factorization to preserve the feasibility in each iteration. However, for some particular cases, the proposals do not require the use of any projection operator. In addition, we consider a Barzilai and Borwein-like step-size combined with the Zhang-Hager nonmonotone line-search technique in order to accelerate the convergence of the proposed procedures. We proved the global convergence for these schemes, and we evaluate their effectiveness and efficiency through an extensive computational study, comparing our approaches with other state-of-the-art gradient-type algorithms.
Phasor measurement units (PMUs) are deployed at power grid nodes around the transmission grid, determining precise power system monitoring conditions. In real life, it is not realistic to place a PMU at every power gr...
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Phasor measurement units (PMUs) are deployed at power grid nodes around the transmission grid, determining precise power system monitoring conditions. In real life, it is not realistic to place a PMU at every power grid node;thus, the lowest PMU number is optimally selected for the full observation of the entire network. In this study, the PMU placement model is reconsidered, taking into account single- and multi-capacity placement models rather than the well-studied PMU placement model with an unrestricted number of channels. A restricted number of channels per monitoring device is used, instead of supposing that a PMU is able to observe all incident buses through the transmission connectivity lines. The optimization models are declared closely to the power dominating set and minimum edge cover problem in graph theory. These discrete optimization problems are directly related with the minimum set covering problem. Initially, the allocation model is declared as a constrained mixed-integer linear program implemented by mathematical and stochastic algorithms. Then, the 0/1 integer linear problem is reformulated into a non-convex constraint program to find optimality. The mathematical models are solved either in binary form or in the continuous domain using specialized optimization libraries, and are all implemented in YALMIP software in conjunction with MATLAB. Mixed-integer linear solvers, nonlinear programming solvers, and heuristic algorithms are utilized in the aforementioned software packages to locate the global solution for each instance solved in this application, which considers the transformation of the existing power grids to smart grids.
Magnetically coupled resonance wireless power transmission technology (MCR-WPT), as a technological innovation in the electric vehicle industry, is of great significance to promote the development of the electric vehi...
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Magnetically coupled resonance wireless power transmission technology (MCR-WPT), as a technological innovation in the electric vehicle industry, is of great significance to promote the development of the electric vehicle industry chain. The current wireless charging technology is affected by the design of the vehicle itself, the distance between the vehicle-mounted part of the wireless charging and the ground is not fixed. And the changeable parking attitude will cause the projection of the transmitting coil and the receiving coil to deviate. Therefore, reasonable matching of transmission frequency, matching impedance and other parameters is of great significance for optimizing power transmission efficiency. This paper establishes a mathematical model of transmission frequency, matching impedance, distance between two coils and wireless power transmission efficiency. Based on the preliminary analysis of 10 experimental data of wireless charging in the laboratory under different coil spacings, the relationship between various parameters and wireless charging efficiency is obtained. In view of the problem of coil offset under actual charging conditions, a nonlinear optimization model for maximizing the efficiency of the MCR-WPT system is proposed. The selected optimization parameters are parameters such as transmission frequency and matching impedance. The goal is to ensure the maximum value of automotive coil offset under high transmission efficiency. In this paper, the optimization model is solved based on the Ant lion optimizer, and the optimal parameter values under the specified working conditions are obtained, and the relative error is less than 3#x00025;. When the coil spacing is 10mm, the maximum offset of the coil with a transmission efficiency higher than 80#x00025;is 0.3423m, and the RMSE between theoretical and experimental results is less than 0.015. Algorithm optimizes the power transmission efficiency and improved the fault tolerance rate of wireless ch
Against the shortcomings that many existing algorithms for solving the standard smoothing nonlinear programming would fail if they were used directly to solve the mathematical programs with complementary constraints( ...
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The authors consider the problem of generating spheroidal voids in a three- dimensional domain of complex geometry, with regard for the constraints on the "sparseness" of voids subject to the system balance....
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The authors consider the problem of generating spheroidal voids in a three- dimensional domain of complex geometry, with regard for the constraints on the "sparseness" of voids subject to the system balance. The problem is reduced to the optimized layout of ellipsoids of revolution in a convex container (cylinder or cuboid), taking into account the prohibited zones, constraints on the feasible distances between objects, and the balance condition. The problem is aimed at maximizing the minimum distance between each pair of ellipsoids and each ellipsoid and the boundary of the container. Adjusted quasi-phi-functions for analytical description of the allocation constraints are defined. A mathematical model is constructed in the form of a nonlinear programming problem. A solution method is proposed that uses the multistart strategy in combination with smart algorithms to search for feasible and locally optimal solutions. The results of computating experiments are presented.
Manufacturing systems consume a tremendous amount of energy and contribute about a quarter of greenhouse gas emissions. To achieve the sustainable production, it is vital to reduce the total energy consumption and imp...
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Manufacturing systems consume a tremendous amount of energy and contribute about a quarter of greenhouse gas emissions. To achieve the sustainable production, it is vital to reduce the total energy consumption and improve the energy efficiency of manufacturing systems, especially energy-intensive manufacturing systems. In this paper, the energy consumption optimization problem for a two-machine geometric line is investigated. Specifically, it is formulated as a nonlinear programming which minimizes the energy consumption of the system while maintaining a required production rate. For this nonlinear programming with complex constraints, two optimality equations are explored and their mathematical properties are analyzed. Based on these properties, an effective and computationally efficient algorithm is developed to solve the optimal solution of the energy consumption optimization problem. In addition, the sensitivity of the optimal solution with respect to system parameters is analyzed. Finally, several extensions of the problem with an alternative objective and more practical considerations, are addressed as well.
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