scholarly journals APPLICATION OF THE “JUMPING FROGS” ALGORITHM FOR RESEARCH AND OPTIMIZATION OF THE TECHNOLOGICAL PROCESS

2021 ◽  
Vol 1 (1) ◽  
pp. 57-65
Author(s):  
N. D. Koshevoy ◽  
V. V. Muratov ◽  
A. L. Kirichenko ◽  
S. A. Borisenko
Keyword(s):  
Search Algorithm ◽  
Optimization Methods ◽  
Experiment Planning ◽  
Full Factorial Experiment ◽  
Time Costs ◽  
Optimal Experiment ◽  
Active Experiment ◽  
Initial Cost ◽  
The Cost ◽  
Full Factorial

Context. An application of the method of a “jumping frogs” search algorithm to construct optimal experiment plans for cost (time) in the study of technological processes and systems that allow the implementation of an active experiment on them is proposed. The object of study are optimization methods for cost (time) costs of experimental designs, based on the application of a “jumping frogs” search algorithm. Objective. To obtain optimization results by optimizing the search of a “jumping frogs” search algorithm for the cost (time) costs of plans for a full factorial experiment. Method. A method is proposed for constructing a cost-effective (time) implementation of an experiment planning matrix using algorithms for searching for “jumping frogs”. At the beginning, the number of factors and the cost of transitions for each factor level are entered. Then, taking into account the entered data, the initial experiment planning matrix is formed. Then, taking into account the entered data, the initial matrix of experiment planning is formed. The “jumping frogs” method determines the “successful frog” by the lowest cost of transitions between levels for each of the factors. After that, the permutations of the “frogs” are performed. The “frog” strives for the most “successful” and, provided it stays close, remains in the location. Then the gain is calculated in comparison with the initial cost (time) of the experiment. Results. Software has been developed that implements the proposed method, which was used to conduct computational experiments to study the properties of these methods in the study of technological processes and systems that allow the implementation of an active experiment on them. The experimental designs that are optimal in terms of cost (time) are obtained, and the winnings in the optimization results are compared with the initial cost of the experiment. A comparative analysis of optimization methods for the cost (time) costs of plans for a full factorial experiment is carried out. Conclusions. The conducted experiments confirmed the operability of the proposed method and the software that implements it, and also allows us to recommend it for practical use in constructing optimal experiment planning matrices.

scholarly journals ПРИМЕНЕНИЕ АЛГОРИТМА ПРЫГАЮЩИХ ЛЯГУШЕК ДЛЯ ОПТИМИЗАЦИИ ПО СТОИМОСТНЫМ (ВРЕМЕННЫМ) ЗАТРАТАМ ПЛАНОВ ПОЛНОГО ФАКТОРНОГО ЭКСПЕРИМЕНТА

2018 ◽  
pp. 53-60
Author(s):  
Николай Дмитриевич Кошевой ◽  
Виктор Владимирович Муратов
Keyword(s):  
Combustion Engine ◽  
Experimental Studies ◽  
Factorial Experiment ◽  
Experiment Planning ◽  
Optimal Time ◽  
Full Factorial Experiment ◽  
Time Costs ◽  
Shuffled Frog Leaping ◽  
The Cost ◽  
Full Factorial

The purpose of this article is to further develop the methodology for the optimal cost (time) costs of experiment planning, which includes a set of methods for optimizing experiment plans and software and hardware for their implementation. The object of study: the optimization processes for the cost-based plans of multivariate experiments. The subject of research: the cost-optimization method of experimental design plans, based on the use of shuffled frog-leaping method. Experimental research methods are increasingly used to optimize production processes. Planning an experiment allows you to get their mathematical models with minimal cost and time costs. At the same time, a method and a program in the C ++ programming language were developed for constructing optimal or close to optimal plans for a full factorial experiment applying the shuffled frog-leaping algorithm. This allows you to automate the process of solving the problem, reduce the time to develop optimal plans for the experiment, increase the reliability of the results, reduce the time and cost of the experiments. Its effectiveness is shown in comparison with other methods for optimizing multi-factor experimental designs. The efficiency and effectiveness are confirmed by the coincidence or approximation of the optimal plans obtained by this method and the method of complete enumeration. A number of technological objects are presented on which the operability of the developed method and software was tested, namely: fuel consumption in an internal combustion engine, welding of small thickness plates, production of parts by hot stamping, as well as the process of servicing numerically controlled machines. A comparative analysis of the methods for the synthesis of cost-optimal (time) expenditure plans for a full factorial experiment was carried out and the effectiveness of the shuffled frog-leaping method was shown. It is shown that the difficult task of reducing material and time costs when conducting experimental studies can be solved using the proposed method and the software implementing it.

scholarly journals ИССЛЕДОВАНИЕ И ОПТИМИЗАЦИЯ ВЛИЯНИЯ ФРАКЦИОННОГО СОСТАВА РАБОЧЕЙ СМЕСИ ПОРОШКОВ НА ХАРАКТЕРИСТИКИ ТВЕРДОГО СМЕСЕВОГО РАКЕТНОГО ТОПЛИВА

2020 ◽  
pp. 42-52
Author(s):  
Николай Дмитриевич Кошевой ◽  
Алексей Леонидович Кириченко ◽  
Сергей Анатольевич Борисенко ◽  
Виктор Владимирович Муратов
Keyword(s):  
Fractional Composition ◽  
Time Lapse ◽  
Factorial Experiment ◽  
Experiment Planning ◽  
Rocket Fuel ◽  
Full Factorial Experiment ◽  
Current Location ◽  
Time Optimal ◽  
The Cost ◽  
Full Factorial

When studying the influence of the fractional composition of the working mixture of powders on the characteristics of solid mixed rocket fuel (SMRF), optimization is proposed using the jumping frog method to construct time-optimal experimental designs. It is known that the proportion of the fractional agent (FA) product in the composition of SMRF is the largest and amounts to 80 %. Consequently, the FA product has one of the greatest effects on the whole range of physicochemical properties of SMRF. Thus, the task of determining the effect of the FA product on the properties of SMRF is very relevant. The application of experimental design methods reduces the cost and time costs in the study of various technological processes, devices, and systems. Minimizing the number of transitions of factor levels in terms of the experiment, in turn, leads to a decrease in the cost (time) of its implementation. The goal of the work is the optimization of the full factorial experiment time-lapse experiment using the jumping frog method. To this end, a method is proposed for constructing a time-optimal implementation of the experiment planning matrix using the jumping frog algorithm. In the jumping frog method, a successful frog is determined by the least transition time between levels for each of the factors. After that, frog permutations are performed. The frog strives for the most successful and, if located nearby, remains in its current location. The software has been developed that implements the proposed method, which was used to conduct computational experiments to study the properties of this method when studying the influence of the fractional composition of the working mixture of powders on the characteristics of solid mixed rocket fuel. The experimental plans optimal in terms of implementation time were obtained, and also the winnings in the optimization results are given in comparison with the initial experiment time. A full factorial experiment was carried out to study the effect of the fractional composition of the working mixture of powders on the characteristics of SMRF, based on which recommendations were made regarding the effect of the fractional composition of the working mixture of powders and the content of liquid-viscous components in the composition on the properties of SMRF. Mathematical models are also constructed, the coefficients of which characterize the effect of the content of liquid-viscous components in the composition on the properties of the SMRF. The experiments confirmed the efficiency of the proposed method and the software that implements it, and also allow us to recommend it for practical use in constructing the optimal planning matrices of the experiment.

scholarly journals Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm

2021 ◽  
Vol 11 (10) ◽  
pp. 4438
Author(s):  
Satyendra Singh ◽  
Manoj Fozdar ◽  
Hasmat Malik ◽  
Maria del Valle Fernández Moreno ◽  
Fausto Pedro García Márquez
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Large Scale ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimization Methods ◽  
Bidding Strategy ◽  
Wind Speed Profile ◽  
Gravitational Search ◽  
Modified Gravitational Search Algorithm

It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.

scholarly journals A framework for reducing the overhead of the quantum oracle for use with Grover’s algorithm with applications to cryptanalysis of SIKE

2020 ◽  
Vol 15 (1) ◽  
pp. 143-156
Author(s):  
Jean-François Biasse ◽  
Benjamin Pring
Keyword(s):  
Search Algorithm ◽  
Circuit Complexity ◽  
Quantum Circuit ◽  
Grover’S Algorithm ◽  
Search Problems ◽  
Trade Offs ◽  
Single Target ◽  
Grover's Algorithm ◽  
Quantum Oracle ◽  
The Cost

AbstractIn this paper we provide a framework for applying classical search and preprocessing to quantum oracles for use with Grover’s quantum search algorithm in order to lower the quantum circuit-complexity of Grover’s algorithm for single-target search problems. This has the effect (for certain problems) of reducing a portion of the polynomial overhead contributed by the implementation cost of quantum oracles and can be used to provide either strict improvements or advantageous trade-offs in circuit-complexity. Our results indicate that it is possible for quantum oracles for certain single-target preimage search problems to reduce the quantum circuit-size from $O\left(2^{n/2}\cdot mC\right)$ (where C originates from the cost of implementing the quantum oracle) to $O(2^{n/2} \cdot m\sqrt{C})$ without the use of quantum ram, whilst also slightly reducing the number of required qubits.This framework captures a previous optimisation of Grover’s algorithm using preprocessing [21] applied to cryptanalysis, providing new asymptotic analysis. We additionally provide insights and asymptotic improvements on recent cryptanalysis [16] of SIKE [14] via Grover’s algorithm, demonstrating that the speedup applies to this attack and impacting upon quantum security estimates [16] incorporated into the SIKE specification [14].

Analysis of the Permanent Magnet Guideway of High Temperature Superconducting Maglev

2013 ◽  
Vol 745-746 ◽  
pp. 197-202 ◽  
Author(s):  
Chang Qing Ye ◽  
Zi Gang Deng ◽  
Jia Su Wang
Keyword(s):  
High Temperature ◽  
Permanent Magnet ◽  
High Speed ◽  
Optimization Design ◽  
Optimization Methods ◽  
High Temperature Superconducting ◽  
Practical Engineering ◽  
Hts Maglev ◽  
Ndfeb Permanent Magnet ◽  
The Cost

t was theoretically and experimentally proved that High Temperature Superconducting (HTS) Maglev had huge potential employment in rail transportation and high speed launch system. This had attracted great research interests in practical engineering. The optimization design was one of the most important works in the application of the HTS Maglev. As the NdFeB permanent magnet and HTS materials prices increased constantly, the design optimization of the permanent guideway (PMG) of HTS maglev became one of the indispensable works to decrease the cost of the application. This paper first reviewed four types of PMGs used by the HTS Maglev, then disucssed their structures and magnetic fields. Finally, the optimization methods of these four PMGs were compared. It was suggested that with better optimization methods, the levitation performance within a limit cost got better. That would be helpful to the future numerical optimization of the PMG of the HTS maglev.

Principles of exposure of polymer materials to heat, moisture and UV-radiation and study of their properties by full factorial experiment: A review

2021 ◽  
pp. 146-160
Author(s):  
A. B. Laptev ◽  
A. S. Nesterov ◽  
A. M. Vardanyan ◽  
A. M. Vardanyan
Keyword(s):  
Uv Radiation ◽  
Climatic Factors ◽  
Initial Period ◽  
Amorphous State ◽  
Surface Oxidation ◽  
Polymer Chains ◽  
Factorial Experiment ◽  
Polymer Materials ◽  
Full Factorial Experiment ◽  
Full Factorial

The work is dedicated to the effects of climatic factors on polyethylene terephthalate (PET) in terms of changes in the structure and interaction of polymer molecules. The kinetic concept of the strength of PET has been developed, and the factors influencing the strength have been considered. Effects of moisture, thermal oxidative destruction, and UV-radiation on the structure of PET have been investigated. Polymers’ properties predicting, durability and their computer modeling have been analyzed. A model of changes in PET properties under the influence of temperature, moisture and UV-radiation was constructed using the methods of a full factorial experiment. It has been shown that in the initial period of exposure, adsorption and diffusion of moisture, hydrolysis and surface oxidation occur; prolonged and constant exposure to UV-radiation break the bonds formed by moisture, then the C–C and C–O bonds in the PET molecule brake and new intermolecular bonds are formed. In the amorphous state of PET, the breaking of bonds in the polymer chain and the formation of bonds between two adjacent polymer chains, the formation of more densely packed nodes, the destruction of the polymer and its aging, are equally probable. Temperature has a secondary effect, facilitating both hydrolysis and oxidation and polymer degradation.

scholarly journals The influence of technological parameters for the production of plasticized polyvinylbutyral films on their optical and physico-mechanical properties

2019 ◽  
pp. 7-8
Author(s):  
M. M. Egorov ◽  
V. I. Milov ◽  
M. K. Timin ◽  
T. P. Mukhina ◽  
V. S. Smirnov ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Mathematical Analysis ◽  
Polyvinyl Butyral ◽  
Factorial Experiment ◽  
Regression Equations ◽  
Technological Parameters ◽  
Full Factorial Experiment ◽  
Effect Of Pressure ◽  
Direct Pressing ◽  
Full Factorial

The effect of pressure, temperature and time during direct pressing on the strength and optical characteristics of adhesive plasticized polyvinyl butyral films is studied. A mathematical analysis of the results of a full factorial experiment is carried out and the regression equations are derived.

scholarly journals Aero-Structural Optimization of Joined-Wing Aircraft

2017 ◽  
Vol 2017 (4) ◽  
pp. 48-63
Author(s):  
Miłosz Kalinowski
Keyword(s):  
Structural Optimization ◽  
Search Algorithm ◽  
Optimization Methods ◽  
Global Search ◽  
Preliminary Design ◽  
Electric Aircraft ◽  
Modular Algorithm ◽  
Lifting Surfaces ◽  
Joined Wing ◽  
Aircraft Configurations

Abstract Joined-wing aircraft due to its energy characteristics is a suitable configuration for electric aircraft when designed properly. However, because of the specific for this aircraft phenomenons (e.g. static indeterminacy of structure, aerodynamic interference of lifting surfaces) it demands more complicated methods to model its behavior than a traditional aircraft configurations. For these reasons the aero-structural optimization process is proposed for joined-wing aircrafts that is suitable for preliminary design. The process is a global search, modular algorithm based on automatic geometry generator, FEM solver and aerodynamic panel method. The range of aircraft was assumed as an objective function. The algorithm was successfully tested on UAV aircraft. The improvement of 19% of total aircraft range is achieved in comparison to baseline aircraft. Time of evaluation of this global search algorithm is similar to the time characteristic for local optimization methods. It allows to reduce the time and costs of preliminary design of joined-wing.

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