In this paper, we propose two new perturbation simplex variants. Solving linear programming problems without introducing artificial variables, each of the two uses the dual pivot rule to achieve primal feasibility, an...In this paper, we propose two new perturbation simplex variants. Solving linear programming problems without introducing artificial variables, each of the two uses the dual pivot rule to achieve primal feasibility, and then the primal pivot rule to achieve optimality. The second algorithm, a modification of the first, is designed to handle highly degenerate problems more efficiently. Some interesting results concerning merit of the perturbation are established. Numerical results from preliminary tests are also reported. [ABSTRACT FROM AUTHOR]展开更多
This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,c...This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changing the state of the PRO in terms of self-strengthening.Furthermore,the Nelder-Mead simplex is used to optimize the best agent in the population,accelerating the convergence speed and improving the accuracy of the PRO population.By comparing LNPRO with nine advanced algorithms in the IEEE CEC 2022 benchmark function,the convergence accuracy of the LNPRO has been verified.The accuracy and stability of simulated data and real data in the parameter extraction of PV systems are crucial.Compared to the PRO,the precision and stability of LNPRO have indeed been enhanced in four types of photovoltaic components,and it is also superior to other excellent algorithms.To further verify the parameter extraction problem of LNPRO in complex environments,LNPRO has been applied to three types of manufacturer data,demonstrating excellent results under varying irradiation and temperatures.In summary,LNPRO holds immense potential in solving the parameter extraction problems in PV systems.展开更多
First, the main procedures and the distinctive features of the most-obtuse-angle（MOA）row or column pivot rules are introduced for achieving primal or dual feasibility in linear programming. Then, two special auxilia...First, the main procedures and the distinctive features of the most-obtuse-angle（MOA）row or column pivot rules are introduced for achieving primal or dual feasibility in linear programming. Then, two special auxiliary problems are constructed to prove that each of the rules can be actually considered as a simplex approach for solving the corresponding auxiliary problem. In addition, the nested pricing rule is also reviewed and its geometric interpretation is offered based on the heuristic characterization of an optimal solution.展开更多
The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear programming problem (LP). O...The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear programming problem (LP). One of the important steps of the simplex algorithm is applying an appropriate pivot rule to select the basis-entering variable corresponding to the maximum reduced cost. Unfortunately, this pivot rule not only can lead to a critical cycling (solved by Bland’s rules), but does not improve efficiently the objective function. Our new pivot rule 1) solves the cycling problem in the original Dantzig’s simplex pivot rule, and 2) leads to an optimal improvement of the objective function at each iteration. The new pivot rule can lead to the optimal solution of LP with a lower number of iterations. In a maximization problem, Dantzig’s pivot rule selects a basis-entering variable corresponding to the most positive reduced cost;in some problems, it is well-known that Dantzig’s pivot rule, before reaching the optimal solution, may visit a large number of extreme points. Our goal is to improve the simplex algorithm so that the number of extreme points to visit is reduced;we propose an optimal improvement in the objective value per unit step of the basis-entering variable. In this paper, we propose a pivot rule that can reduce the number of such iterations over the Dantzig’s pivot rule and prevent cycling in the simplex algorithm. The idea is to have the maximum improvement in the objective value function: from the set of basis-entering variables with positive reduced cost, the efficient basis-entering variable corresponds to an optimal improvement of the objective function. Using computational complexity arguments and some examples, we prove that our optimal pivot rule is very effective and solves the cycling problem in LP. We test and compare the efficiency of this new pivot rule with Dantzig’s original pivot rule and the simplex algorithm in MATLAB environment.展开更多
The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And...The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.展开更多
Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of ...Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of large thin-walled components,machining deformation of component is easy to exceed the specification.In order to address the problem,it is important to retain the appropriate finishing allowance.To find the overall machining deformation,finishing allowance-induced deformation(web finishing allowance,sidewall finishing allowance)and initial residual stress-induced deformation were considered as major factors.Meanwhile,machined surface residual stress-induced deformation,clamping stress-induced deformation,thermal deformation,gravity-induced deformation and inertial force-induced deformation were neglected in the optimization model.Six-peak Gaussian function was introduced to fit the initial residual stress.Based upon the obtained function of initial residual stress,a deformation prediction model between initial residual stress and finishing allowance was established to attain the finishing allowanceinduced deformation.In addition,linear programming optimization model based on the simplex algorithm was developed to optimize the overall machining deformation.Results have concluded that the overall machining deformation reached the minimum value when sidewall finishing allowance and web finishing allowance varied between 1 and 2 mm.Additionally,web finishing allowance-induced deformation and sidewall finishing allowance-induced deformation were1.05 mm and 0.7 mm.Furthermore,the machining deformation decreased to 0.3–0.38 mm with the application of optimized finishing allowance allocation strategy,which made 39–56%reduction of the overall machining deformation compared to that in conventional method.展开更多
We developed a mathematical optimization model coupling chemical compositions and high-temperature characteristics of sintering materials, targeting the best quality and lowest cost. The simplex algorithm was adopted ...We developed a mathematical optimization model coupling chemical compositions and high-temperature characteristics of sintering materials, targeting the best quality and lowest cost. The simplex algorithm was adopted to solve this model. Four kinds of imported iron ores, two kinds of Chinese iron ore concentrates, and two kinds of fluxes were selected to verify both the model and the algorithm. The results confirmed the possibility of considering both chemical compositions and high-temperature characteristics of iron ores in the optimization model. This model provides a technical roadmap to obtain a precise mathematical correlation between the lowest cost and the grade of iron in sinters based on the condition of given raw materials, which can provide a reference to adjust the grade of iron in the sintering process for enterprise.展开更多
In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and r...In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.展开更多
A robust phase-only Direct Data Domain Least Squares (D3LS) algorithm based on gen- eralized Rayleigh quotient optimization using hybrid Genetic Algorithm (GA) is presented in this letter. The optimization efficiency ...A robust phase-only Direct Data Domain Least Squares (D3LS) algorithm based on gen- eralized Rayleigh quotient optimization using hybrid Genetic Algorithm (GA) is presented in this letter. The optimization efficiency and computational speed are improved via the hybrid GA com- posed of standard GA and Nelder-Mead simplex algorithms. First, the objective function, with a form of generalized Rayleigh quotient, is derived via the standard D3LS algorithm. It is then taken as a fitness function and the unknown phases of all adaptive weights are taken as decision variables. Then, the nonlinear optimization is performed via the hybrid GA to obtain the optimized solution of phase-only adaptive weights. As a phase-only adaptive algorithm, the proposed algorithm is sim- pler than conventional algorithms when it comes to hardware implementation. Moreover, it proc- esses only a single snapshot data as opposed to forming sample covariance matrix and operating matrix inversion. Simulation results show that the proposed algorithm has a good signal recovery and interferences nulling performance, which are superior to that of the phase-only D3LS algorithm based on standard GA.展开更多
Based on simplex algorithm of optimal design, the multicomponent mixture regression model was used to investigate physical properties of submerged arc welding flux. The effect of complex interaction of seven component...Based on simplex algorithm of optimal design, the multicomponent mixture regression model was used to investigate physical properties of submerged arc welding flux. The effect of complex interaction of seven components in agglomerated flux on softening temperature was analyzed. The results indicate that the interaction of MgO-TiO2-CaCOa-AI20a increases the softening temperature of flux, but the additions of CaF2 and ZrO2 can decrease the softening temperature.展开更多
A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which in...A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed, Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.展开更多
The traditional genetic algorithm(GA)has unstable inversion results and is easy to fall into the local optimum when inverting fault parameters.Therefore,this article considers the combination of GA with other non-line...The traditional genetic algorithm(GA)has unstable inversion results and is easy to fall into the local optimum when inverting fault parameters.Therefore,this article considers the combination of GA with other non-linear algorithms in order to improve the inversion precision of GA.This paper proposes a genetic Nelder-Mead neural network algorithm(GNMNNA).This algorithm uses a neural network algorithm(NNA)to optimize the global search ability of GA.At the same time,the simplex algorithm is used to optimize the local search capability of the GA.Through numerical examples,the stability of the inversion algorithm under different strategies is explored.The experimental results show that the proposed GNMNNA has stronger inversion stability and higher precision compared with the existing algorithms.The effectiveness of GNMNNA is verified by the BodrumeKos earthquake and Monte Cristo Range earthquake.The experimental results show that GNMNNA is superior to GA and NNA in both inversion precision and computational stability.Therefore,GNMNNA has greater application potential in complex earthquake environment.展开更多
Microtremors array observation for estimating S-wave velocity structure from phase velocities of Rayleigh and Love wave on two practical sites in Tangshan area by a China-US joint group are researched.The phase veloci...Microtremors array observation for estimating S-wave velocity structure from phase velocities of Rayleigh and Love wave on two practical sites in Tangshan area by a China-US joint group are researched.The phase velocities of Rayleigh wave are estimated from vertical component records and those of Love wave are estimated from three-component records of microtremors array using modified spatial auto-correlation method.Haskell matrix method is used in calculating Rayleigh and Love wave phase velocities,and the shallow S-wave velocity structure of two practical sites are estimated by means of a hybrid approach of Genetic Algorithm and Simplex.The results are compared with the PS logging data of the two sites,showing it is feasible to estimate the shallow S-wave velocity structure of practical site from the observation of microtremor array.展开更多
This study aimed to optimize cross-sectional area of the extruder and the flow rate of the material through the extruder. Extrusion process was first modelized using the continuum mechanics method before being simulat...This study aimed to optimize cross-sectional area of the extruder and the flow rate of the material through the extruder. Extrusion process was first modelized using the continuum mechanics method before being simulated with the commercial software LS-DYNA using the Johnson-Cook model based on the finite element method after optimization of the factors with simplex algorithm. The study was carried out on a connecting rod: diameter of 145 mm, cross-section of 1.65 m<sup>2</sup>, length of 0.25 m, volume of 0.41 m<sup>3</sup> and a mass of 37 kg. Optimum parameters obtained were temperature of 850℃, flow rate of 0.237 m/s, die diameter of 19.2 mm, pin diameter of 14 mm, extrusion strength of 565.6 kN and press pressure of 245 GPa. From these factors, a blank was obtained with external and internal diameters of 19.2 and 14 mm respectively over a length of 28 m with a thickness of 2.6 mm. Simulation using LS-DYNA software resulted in a difference in values of 7.4% between optimization and simulation when the difference of 2.4% was found between modelling and simulation. These values make the process optimal for industrial application to improve the extrusion requirements of copper tubes.展开更多
The algorithm under this name, together with the variants, is a method that solves the problems of optimal flow and costs. Examples of such problems are planning and procurement, scheduling by contractors, distributio...The algorithm under this name, together with the variants, is a method that solves the problems of optimal flow and costs. Examples of such problems are planning and procurement, scheduling by contractors, distribution and supply systems, transport on the road or rail network, electricity transmission, computer and telecommunications networks, pipe transmission systems (water, oil, …), and the like. The main goal of any business organization is to increase profits and satisfy its customers. Because business is an integral part of our environment, their goals will be limited by certain environmental factors and economic conditions. The out-of-kilter algorithm is used to solve a complex allocation problem involving interactive and conflicting personal choices subject to interactive resource constraints. The paper presents an example of successful use of this algorithm and proposes an extension to the areas of corporate and social planning. Customer demand, warehousing, and factory capacity were used as input for the model. First, we propose a linear programming approach to determine the optimal distribution pattern to reduce overall distribution costs. The proposed model of linear programming is solved by the standard simplex algorithm and the Excel-solver program. It is noticed that the proposed model of linear programming is suitable for finding the optimal distribution pattern and total minimum costs.展开更多
With the progress of human society,the development of architectural features is also very fast.The research on the era of building features under the construction of“table shape”and“ideology”has received great att...With the progress of human society,the development of architectural features is also very fast.The research on the era of building features under the construction of“table shape”and“ideology”has received great attention.The form of architectural features is accumulated over many years,and the accumulated experience is not available in other ways.The transformation of form and meaning is relative.According to the different architectural structures obtained from the macroscopic and microscopic differences,a unique architectural feature is formed.The simple algorithm is used to construct the system model of the building characteristics of the era of Linyi in order to better analyze,in order to improve our country’s architectural influence.展开更多
We apply the simplex algorithm which is a branch of linear programming to efficiently determine the allocation of resources required to operate a company in the software development field. The main aim of applying thi...We apply the simplex algorithm which is a branch of linear programming to efficiently determine the allocation of resources required to operate a company in the software development field. The main aim of applying this technique is to maximize the profit of a company under certain limitations. This <span>can be done using the trial-and-error approach. However, this tedious</span> process can be replaced by user-level tools such as Excel which are based on linear programming that will give more accurate results. Small software companies cannot afford to hire a high number of senior programmers to produce the required level of quality and to keep up with the demand for adding new features. On the other hand, lowering the quality of the product will reduce the number of customers and decrease profit. Another aspect is maximizing the utilization of hosting servers which are required for providing the services to customers since the cost of buying servers and maintaining them is extremely high. The simplex algorithm in linear programming will take the specified <span>constraints into account to compute the optimal allocation of the available</span> <span>resources to maximize profit and limit the cost. This paper will present a</span> <span>model that uses the simplex algorithm with a set of constraints to determine</span> how many projects of each type a company should take in one period of time.展开更多
Recently, computational results demonstrated remarkable superiority of a so-called ＂largest-distance＂ rule and ＂nested pricing＂ rule to other major rules commonly used in practice, such as Dantzig＇s original rule...Recently, computational results demonstrated remarkable superiority of a so-called ＂largest-distance＂ rule and ＂nested pricing＂ rule to other major rules commonly used in practice, such as Dantzig＇s original rule, the steepest-edge rule and Devex rule. Our computational experiments show that the simplex algorithm using a combination of these rules turned out to be even more efficient.展开更多
Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA...Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.展开更多
This paper works on a modified simplex algorithm for the local optimization of Continuous Piece Wise Linear（CPWL） programming with generalization of hinging hyperplane objective and linear constraints. CPWL programm...This paper works on a modified simplex algorithm for the local optimization of Continuous Piece Wise Linear（CPWL） programming with generalization of hinging hyperplane objective and linear constraints. CPWL programming is popular since it can be equivalently transformed into difference of convex functions programming or concave optimization. Inspired by the concavity of the concave CPWL functions, we propose an Objective Variation Simplex Algorithm（OVSA）, which is able to find a local optimum in a reasonable time. Computational results are presented for further insights into the performance of the OVSA compared with two other algorithms on random test problems.展开更多
文摘In this paper, we propose two new perturbation simplex variants. Solving linear programming problems without introducing artificial variables, each of the two uses the dual pivot rule to achieve primal feasibility, and then the primal pivot rule to achieve optimality. The second algorithm, a modification of the first, is designed to handle highly degenerate problems more efficiently. Some interesting results concerning merit of the perturbation are established. Numerical results from preliminary tests are also reported. [ABSTRACT FROM AUTHOR]
基金supported in part by the Natural Science Foundation of Zhejiang Province(LTGS23E070001).
文摘This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changing the state of the PRO in terms of self-strengthening.Furthermore,the Nelder-Mead simplex is used to optimize the best agent in the population,accelerating the convergence speed and improving the accuracy of the PRO population.By comparing LNPRO with nine advanced algorithms in the IEEE CEC 2022 benchmark function,the convergence accuracy of the LNPRO has been verified.The accuracy and stability of simulated data and real data in the parameter extraction of PV systems are crucial.Compared to the PRO,the precision and stability of LNPRO have indeed been enhanced in four types of photovoltaic components,and it is also superior to other excellent algorithms.To further verify the parameter extraction problem of LNPRO in complex environments,LNPRO has been applied to three types of manufacturer data,demonstrating excellent results under varying irradiation and temperatures.In summary,LNPRO holds immense potential in solving the parameter extraction problems in PV systems.
基金The National Natural Science Foundation of China(No.10371017).
文摘First, the main procedures and the distinctive features of the most-obtuse-angle（MOA）row or column pivot rules are introduced for achieving primal or dual feasibility in linear programming. Then, two special auxiliary problems are constructed to prove that each of the rules can be actually considered as a simplex approach for solving the corresponding auxiliary problem. In addition, the nested pricing rule is also reviewed and its geometric interpretation is offered based on the heuristic characterization of an optimal solution.
文摘The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear programming problem (LP). One of the important steps of the simplex algorithm is applying an appropriate pivot rule to select the basis-entering variable corresponding to the maximum reduced cost. Unfortunately, this pivot rule not only can lead to a critical cycling (solved by Bland’s rules), but does not improve efficiently the objective function. Our new pivot rule 1) solves the cycling problem in the original Dantzig’s simplex pivot rule, and 2) leads to an optimal improvement of the objective function at each iteration. The new pivot rule can lead to the optimal solution of LP with a lower number of iterations. In a maximization problem, Dantzig’s pivot rule selects a basis-entering variable corresponding to the most positive reduced cost;in some problems, it is well-known that Dantzig’s pivot rule, before reaching the optimal solution, may visit a large number of extreme points. Our goal is to improve the simplex algorithm so that the number of extreme points to visit is reduced;we propose an optimal improvement in the objective value per unit step of the basis-entering variable. In this paper, we propose a pivot rule that can reduce the number of such iterations over the Dantzig’s pivot rule and prevent cycling in the simplex algorithm. The idea is to have the maximum improvement in the objective value function: from the set of basis-entering variables with positive reduced cost, the efficient basis-entering variable corresponds to an optimal improvement of the objective function. Using computational complexity arguments and some examples, we prove that our optimal pivot rule is very effective and solves the cycling problem in LP. We test and compare the efficiency of this new pivot rule with Dantzig’s original pivot rule and the simplex algorithm in MATLAB environment.
文摘The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.
基金co-supported by the National Natural Science Foundation of China(No.51405226)Postgraduate Research&Practice Innovation Program of Jiangsu Province of China(No.KYCX19_0165)。
文摘Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of large thin-walled components,machining deformation of component is easy to exceed the specification.In order to address the problem,it is important to retain the appropriate finishing allowance.To find the overall machining deformation,finishing allowance-induced deformation(web finishing allowance,sidewall finishing allowance)and initial residual stress-induced deformation were considered as major factors.Meanwhile,machined surface residual stress-induced deformation,clamping stress-induced deformation,thermal deformation,gravity-induced deformation and inertial force-induced deformation were neglected in the optimization model.Six-peak Gaussian function was introduced to fit the initial residual stress.Based upon the obtained function of initial residual stress,a deformation prediction model between initial residual stress and finishing allowance was established to attain the finishing allowanceinduced deformation.In addition,linear programming optimization model based on the simplex algorithm was developed to optimize the overall machining deformation.Results have concluded that the overall machining deformation reached the minimum value when sidewall finishing allowance and web finishing allowance varied between 1 and 2 mm.Additionally,web finishing allowance-induced deformation and sidewall finishing allowance-induced deformation were1.05 mm and 0.7 mm.Furthermore,the machining deformation decreased to 0.3–0.38 mm with the application of optimized finishing allowance allocation strategy,which made 39–56%reduction of the overall machining deformation compared to that in conventional method.
基金financially supported by the National Natural Science Foundation of China and Baosteel Group Co., Ltd., of Shanghai (U1260202)the Postdoctoral Science Foundation of China (2012T50045)
文摘We developed a mathematical optimization model coupling chemical compositions and high-temperature characteristics of sintering materials, targeting the best quality and lowest cost. The simplex algorithm was adopted to solve this model. Four kinds of imported iron ores, two kinds of Chinese iron ore concentrates, and two kinds of fluxes were selected to verify both the model and the algorithm. The results confirmed the possibility of considering both chemical compositions and high-temperature characteristics of iron ores in the optimization model. This model provides a technical roadmap to obtain a precise mathematical correlation between the lowest cost and the grade of iron in sinters based on the condition of given raw materials, which can provide a reference to adjust the grade of iron in the sintering process for enterprise.
基金Project(51074051)supported by the National Natural Science Foundation of ChinaProject(N110307001)supported by the Fundamental Research Funds for the Central Universities,China
文摘In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.
基金Supported by the Natural Science Foundation of Jiangsu Province (No.BK2004016).
文摘A robust phase-only Direct Data Domain Least Squares (D3LS) algorithm based on gen- eralized Rayleigh quotient optimization using hybrid Genetic Algorithm (GA) is presented in this letter. The optimization efficiency and computational speed are improved via the hybrid GA com- posed of standard GA and Nelder-Mead simplex algorithms. First, the objective function, with a form of generalized Rayleigh quotient, is derived via the standard D3LS algorithm. It is then taken as a fitness function and the unknown phases of all adaptive weights are taken as decision variables. Then, the nonlinear optimization is performed via the hybrid GA to obtain the optimized solution of phase-only adaptive weights. As a phase-only adaptive algorithm, the proposed algorithm is sim- pler than conventional algorithms when it comes to hardware implementation. Moreover, it proc- esses only a single snapshot data as opposed to forming sample covariance matrix and operating matrix inversion. Simulation results show that the proposed algorithm has a good signal recovery and interferences nulling performance, which are superior to that of the phase-only D3LS algorithm based on standard GA.
文摘Based on simplex algorithm of optimal design, the multicomponent mixture regression model was used to investigate physical properties of submerged arc welding flux. The effect of complex interaction of seven components in agglomerated flux on softening temperature was analyzed. The results indicate that the interaction of MgO-TiO2-CaCOa-AI20a increases the softening temperature of flux, but the additions of CaF2 and ZrO2 can decrease the softening temperature.
基金Supported by the National Natural Science Foun-dation of China (60273075)
文摘A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed, Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.
基金This manuscript is supported by the National Natural Science Foundation of China(No.42174011,41874001 and 42174011).
文摘The traditional genetic algorithm(GA)has unstable inversion results and is easy to fall into the local optimum when inverting fault parameters.Therefore,this article considers the combination of GA with other non-linear algorithms in order to improve the inversion precision of GA.This paper proposes a genetic Nelder-Mead neural network algorithm(GNMNNA).This algorithm uses a neural network algorithm(NNA)to optimize the global search ability of GA.At the same time,the simplex algorithm is used to optimize the local search capability of the GA.Through numerical examples,the stability of the inversion algorithm under different strategies is explored.The experimental results show that the proposed GNMNNA has stronger inversion stability and higher precision compared with the existing algorithms.The effectiveness of GNMNNA is verified by the BodrumeKos earthquake and Monte Cristo Range earthquake.The experimental results show that GNMNNA is superior to GA and NNA in both inversion precision and computational stability.Therefore,GNMNNA has greater application potential in complex earthquake environment.
基金Supported by National Natural Science Foundation of China(No.50378032and No.50538030)Associated Foundation of Earthquake Science(No.201009)Foundation of Heilongjiang Institute of Science and Technology(No.04-15).
文摘Microtremors array observation for estimating S-wave velocity structure from phase velocities of Rayleigh and Love wave on two practical sites in Tangshan area by a China-US joint group are researched.The phase velocities of Rayleigh wave are estimated from vertical component records and those of Love wave are estimated from three-component records of microtremors array using modified spatial auto-correlation method.Haskell matrix method is used in calculating Rayleigh and Love wave phase velocities,and the shallow S-wave velocity structure of two practical sites are estimated by means of a hybrid approach of Genetic Algorithm and Simplex.The results are compared with the PS logging data of the two sites,showing it is feasible to estimate the shallow S-wave velocity structure of practical site from the observation of microtremor array.
文摘This study aimed to optimize cross-sectional area of the extruder and the flow rate of the material through the extruder. Extrusion process was first modelized using the continuum mechanics method before being simulated with the commercial software LS-DYNA using the Johnson-Cook model based on the finite element method after optimization of the factors with simplex algorithm. The study was carried out on a connecting rod: diameter of 145 mm, cross-section of 1.65 m<sup>2</sup>, length of 0.25 m, volume of 0.41 m<sup>3</sup> and a mass of 37 kg. Optimum parameters obtained were temperature of 850℃, flow rate of 0.237 m/s, die diameter of 19.2 mm, pin diameter of 14 mm, extrusion strength of 565.6 kN and press pressure of 245 GPa. From these factors, a blank was obtained with external and internal diameters of 19.2 and 14 mm respectively over a length of 28 m with a thickness of 2.6 mm. Simulation using LS-DYNA software resulted in a difference in values of 7.4% between optimization and simulation when the difference of 2.4% was found between modelling and simulation. These values make the process optimal for industrial application to improve the extrusion requirements of copper tubes.
文摘The algorithm under this name, together with the variants, is a method that solves the problems of optimal flow and costs. Examples of such problems are planning and procurement, scheduling by contractors, distribution and supply systems, transport on the road or rail network, electricity transmission, computer and telecommunications networks, pipe transmission systems (water, oil, …), and the like. The main goal of any business organization is to increase profits and satisfy its customers. Because business is an integral part of our environment, their goals will be limited by certain environmental factors and economic conditions. The out-of-kilter algorithm is used to solve a complex allocation problem involving interactive and conflicting personal choices subject to interactive resource constraints. The paper presents an example of successful use of this algorithm and proposes an extension to the areas of corporate and social planning. Customer demand, warehousing, and factory capacity were used as input for the model. First, we propose a linear programming approach to determine the optimal distribution pattern to reduce overall distribution costs. The proposed model of linear programming is solved by the standard simplex algorithm and the Excel-solver program. It is noticed that the proposed model of linear programming is suitable for finding the optimal distribution pattern and total minimum costs.
基金Project Supported by the Brand Professional.Construction of Guangdong Province,Guangdong Province Higher Vocational Education Brand Professional Construction project for Architectural Engineering Technology,2016gzpp016.
文摘With the progress of human society,the development of architectural features is also very fast.The research on the era of building features under the construction of“table shape”and“ideology”has received great attention.The form of architectural features is accumulated over many years,and the accumulated experience is not available in other ways.The transformation of form and meaning is relative.According to the different architectural structures obtained from the macroscopic and microscopic differences,a unique architectural feature is formed.The simple algorithm is used to construct the system model of the building characteristics of the era of Linyi in order to better analyze,in order to improve our country’s architectural influence.
文摘We apply the simplex algorithm which is a branch of linear programming to efficiently determine the allocation of resources required to operate a company in the software development field. The main aim of applying this technique is to maximize the profit of a company under certain limitations. This <span>can be done using the trial-and-error approach. However, this tedious</span> process can be replaced by user-level tools such as Excel which are based on linear programming that will give more accurate results. Small software companies cannot afford to hire a high number of senior programmers to produce the required level of quality and to keep up with the demand for adding new features. On the other hand, lowering the quality of the product will reduce the number of customers and decrease profit. Another aspect is maximizing the utilization of hosting servers which are required for providing the services to customers since the cost of buying servers and maintaining them is extremely high. The simplex algorithm in linear programming will take the specified <span>constraints into account to compute the optimal allocation of the available</span> <span>resources to maximize profit and limit the cost. This paper will present a</span> <span>model that uses the simplex algorithm with a set of constraints to determine</span> how many projects of each type a company should take in one period of time.
基金supported by National Natural Science Foundation of China under the Projects 10871043 and 70971136
文摘Recently, computational results demonstrated remarkable superiority of a so-called ＂largest-distance＂ rule and ＂nested pricing＂ rule to other major rules commonly used in practice, such as Dantzig＇s original rule, the steepest-edge rule and Devex rule. Our computational experiments show that the simplex algorithm using a combination of these rules turned out to be even more efficient.
基金Project supported by the Zhejiang Provincial Natural Science Foundation of China(Nos.LY13F020044 and LZ14F030004)the National Natural Science Foundation of China(No.61571170)
文摘Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.
基金supported by the National Natural Science Foundation of China (Nos. 61473165 and 61134012)the National Key Basic Research and Development (973) Program of China (No. 2012CB720505)
文摘This paper works on a modified simplex algorithm for the local optimization of Continuous Piece Wise Linear（CPWL） programming with generalization of hinging hyperplane objective and linear constraints. CPWL programming is popular since it can be equivalently transformed into difference of convex functions programming or concave optimization. Inspired by the concavity of the concave CPWL functions, we propose an Objective Variation Simplex Algorithm（OVSA）, which is able to find a local optimum in a reasonable time. Computational results are presented for further insights into the performance of the OVSA compared with two other algorithms on random test problems.
