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Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method 被引量:2
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作者 SONG Xiaocheng WANG Jiangtao +3 位作者 WANG Jun SUN Liang FENG Yanghe LI Zhi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第1期129-140,共12页
The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense ... The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense anti-missile targets defense problem is abstracted as a nonconvex constrained combinatorial optimization problem with the optimization objective of maximizing the degree of contribution of the processing scheme to non-cooperative targets, and the constraints mainly consider geographical conditions and anti-missile equipment resources. The grid discretization concept is used to partition the defense area into network nodes, and the overall defense strategy scheme is described as a nonlinear programming problem to solve the minimum defense cost within the maximum defense capability of the defense system network. In the solution of the minimum defense cost problem, the processing scheme, equipment coverage capability, constraints and node cost requirements are characterized, then a nonlinear mathematical model of the non-cooperative target distributed hybrid processing optimization problem is established, and a local optimal solution based on the sequential quadratic programming algorithm is constructed, and the optimal firepower processing scheme is given by using the sequential quadratic programming method containing non-convex quadratic equations and inequality constraints. Finally, the effectiveness of the proposed method is verified by simulation examples. 展开更多
关键词 non-cooperative target distributed hybrid processing multiple constraint minimum defense cost sequential quadratic programming
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Solving Multi-Objective Linear Programming Problem by Statistical Averaging Method with the Help of Fuzzy Programming Method
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作者 Samsun Nahar Marin Akter Md. Abdul Alim 《American Journal of Operations Research》 2023年第2期19-32,共14页
A multi-objective linear programming problem is made from fuzzy linear programming problem. It is due the fact that it is used fuzzy programming method during the solution. The Multi objective linear programming probl... A multi-objective linear programming problem is made from fuzzy linear programming problem. It is due the fact that it is used fuzzy programming method during the solution. The Multi objective linear programming problem can be converted into the single objective function by various methods as Chandra Sen’s method, weighted sum method, ranking function method, statistical averaging method. In this paper, Chandra Sen’s method and statistical averaging method both are used here for making single objective function from multi-objective function. Two multi-objective programming problems are solved to verify the result. One is numerical example and the other is real life example. Then the problems are solved by ordinary simplex method and fuzzy programming method. It can be seen that fuzzy programming method gives better optimal values than the ordinary simplex method. 展开更多
关键词 Fuzzy programming Method Fuzzy Linear programming Problem multi-objective Linear programming Problem Statistical Averaging Method New Statistical Averaging Method
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Priority approach based on quadratic programming model to fuzzy preference relation 被引量:1
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作者 徐泽水 达庆利 陈琦 《Journal of Southeast University(English Edition)》 EI CAS 2005年第1期108-110,共3页
We investigate the decision-making problem with a finite set of alternatives,in which the decision information takes the form of a fuzzy preference relation. We develop asimple and practical approach to obtaining the ... We investigate the decision-making problem with a finite set of alternatives,in which the decision information takes the form of a fuzzy preference relation. We develop asimple and practical approach to obtaining the priority vector of a fuzzy preference relation. Theprominent characteristic of the developed approach is that the priority vector can generally beobtained by a simple formula, which is derived from a quadratic programming model. We utilize theconsistency ratio to check the consistency of fuzzy preference relation. If the fuzzy preferencerelation is of unacceptable consistency, then we can return it to the decision maker to reconsiderstructuring a new fuzzy preference relation until the fuzzy preference relation with acceptableconsistency is obtained. We finally illustrate the priority approach by two numerical examples. Thenumerical results show that the developed approach is straightforward, effective, and can easily beperformed on a computer. 展开更多
关键词 decision making fuzzy preference relation quadratic programming PRIORITY
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A Modified Lagrange Method for Solving Convex Quadratic Optimization Problems
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作者 Twum B. Stephen Avoka John Christian J. Etwire 《Open Journal of Optimization》 2024年第1期1-20,共20页
In this paper, a modified version of the Classical Lagrange Multiplier method is developed for convex quadratic optimization problems. The method, which is evolved from the first order derivative test for optimality o... In this paper, a modified version of the Classical Lagrange Multiplier method is developed for convex quadratic optimization problems. The method, which is evolved from the first order derivative test for optimality of the Lagrangian function with respect to the primary variables of the problem, decomposes the solution process into two independent ones, in which the primary variables are solved for independently, and then the secondary variables, which are the Lagrange multipliers, are solved for, afterward. This is an innovation that leads to solving independently two simpler systems of equations involving the primary variables only, on one hand, and the secondary ones on the other. Solutions obtained for small sized problems (as preliminary test of the method) demonstrate that the new method is generally effective in producing the required solutions. 展开更多
关键词 quadratic programming Lagrangian Function Lagrange Multipliers Optimality Conditions Subsidiary Equations Modified Lagrange Method
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Design and analysis of recurrent neural network models with non-linear activation functions for solving time-varying quadratic programming problems 被引量:11
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作者 Xiaoyan Zhang Liangming Chen +3 位作者 Shuai Li Predrag Stanimirovic Jiliang Zhang Long Jin 《CAAI Transactions on Intelligence Technology》 EI 2021年第4期394-404,共11页
A special recurrent neural network(RNN),that is the zeroing neural network(ZNN),is adopted to find solutions to time-varying quadratic programming(TVQP)problems with equality and inequality constraints.Howevet,there a... A special recurrent neural network(RNN),that is the zeroing neural network(ZNN),is adopted to find solutions to time-varying quadratic programming(TVQP)problems with equality and inequality constraints.Howevet,there are some weaknesses in activation functions of traditional ZNN models,including convex restriction and redundant formulation.With the aid of different activation functions,modified ZNN models are obtained to overcome the drawbacks for solving TVQP problems.Theoretical and experimental research indicate that the proposed models are better and more effective at solving such TVQP problems. 展开更多
关键词 activation programming quadratic
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A POLYNOMIAL PREDICTOR-CORRECTOR INTERIOR-POINT ALGORITHM FOR CONVEX QUADRATIC PROGRAMMING 被引量:4
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作者 余谦 黄崇超 江燕 《Acta Mathematica Scientia》 SCIE CSCD 2006年第2期265-270,共6页
This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one c... This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one corrector step after each predictor step, where Step 2 is a predictor step and Step 4 is a corrector step in the algorithm. In the algorithm, the predictor step decreases the dual gap as much as possible in a wider neighborhood of the central path and the corrector step draws iteration points back to a narrower neighborhood and make a reduction for the dual gap. It is shown that the algorithm has O(√nL) iteration complexity which is the best result for convex quadratic programming so far. 展开更多
关键词 Convex quadratic programming PREDICTOR-CORRECTOR interior-point algorithm
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Orthogonal genetic algorithm for solving quadratic bilevel programming problems 被引量:4
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作者 Hong Li Yongchang Jiao Li Zhang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2010年第5期763-770,共8页
A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker(KKT) conditions.To cope with the complementarity constraints,a binary encod... A quadratic bilevel programming problem is transformed into a single level complementarity slackness problem by applying Karush-Kuhn-Tucker(KKT) conditions.To cope with the complementarity constraints,a binary encoding scheme is adopted for KKT multipliers,and then the complementarity slackness problem is simplified to successive quadratic programming problems,which can be solved by many algorithms available.Based on 0-1 binary encoding,an orthogonal genetic algorithm,in which the orthogonal experimental design with both two-level orthogonal array and factor analysis is used as crossover operator,is proposed.Numerical experiments on 10 benchmark examples show that the orthogonal genetic algorithm can find global optimal solutions of quadratic bilevel programming problems with high accuracy in a small number of iterations. 展开更多
关键词 orthogonal genetic algorithm quadratic bilevel programming problem Karush-Kuhn-Tucker conditions orthogonal experimental design global optimal solution.
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A COMBINED PARAMETRIC QUADRATIC PROGRAMMING AND PRECISE INTEGRATION METHOD BASED DYNAMIC ANALYSIS OF ELASTIC-PLASTIC HARDENING/SOFTENING PROBLEMS 被引量:3
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作者 张洪武 张新伟 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2002年第6期638-648,共11页
The objective of the paper is to develop a new algorithm for numerical solution of dynamic elastic-plastic strain hardening/softening problems. The gradient dependent model is adopted in the numerical model to overcom... The objective of the paper is to develop a new algorithm for numerical solution of dynamic elastic-plastic strain hardening/softening problems. The gradient dependent model is adopted in the numerical model to overcome the result mesh-sensitivity problem in the dynamic strain softening or strain localization analysis. The equations for the dynamic elastic-plastic problems are derived in terms of the parametric variational principle, which is valid for associated, non-associated and strain softening plastic constitutive models in the finite element analysis. The precise integration method, which has been widely used for discretization in time domain of the linear problems, is introduced for the solution of dynamic nonlinear equations. The new algorithm proposed is based on the combination of the parametric quadratic programming method and the precise integration method and has all the advantages in both of the algorithms. Results of numerical examples demonstrate not only the validity, but also the advantages of the algorithm proposed for the numerical solution of nonlinear dynamic problems. 展开更多
关键词 precise integration method parametric quadratic programming method strain localization strain softening dynamic response
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Principal-subordinate hierarchical multi-objective programming model of initial water rights allocation 被引量:5
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作者 Dan WU Feng-ping WU Yan-ping CHEN 《Water Science and Engineering》 EI CAS 2009年第2期105-116,共12页
The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and wate... The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model. 展开更多
关键词 initial water rights allocation principal-subordinate hierarchy multi-objective programming model satisfaction degree
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Global optimality conditions for quadratic 0-1 programming with inequality constraints 被引量:1
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作者 张连生 陈伟 姚奕荣 《Journal of Shanghai University(English Edition)》 CAS 2010年第2期150-154,共5页
Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are present... Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are presented.The necessary condition is expressed without dual variables.The relations between the global optimal solutions of nonconvex quadratic 0-1 problems and the associated relaxed convex problems are also studied. 展开更多
关键词 quadratic 0-1 programming optimality condition nonconvex optimization integer programming convex duality
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A Quadratic Programming Model for Blast Scheduling 被引量:1
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作者 Chunyan Meng Samuel Frimpong Mingjian Zuo(Ph. D. Student (correspondent). 606-Chemical-Mineral Building. Dept of Civil and Environmental Engineering. University of Alberta. T6G 2G6.Edmonton, AB. Canada)(Associate protessor, School of Mining and Petrole 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 1999年第3期165-167,共3页
A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' pa... A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems. 展开更多
关键词 quadratic programming open pit mining blast scheduling mine production scheduling mathematical programming model
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Genetic Algorithm for Solving Quadratic Bilevel Programming Problem 被引量:1
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作者 WANG Guangmin WAN Zhongping +1 位作者 WANG Xianjiai FANG Debin 《Wuhan University Journal of Natural Sciences》 CAS 2007年第3期421-425,共5页
By applying Kuhn-Tucker condition the quadratic bilevel programming, a class of bilevel programming, is transformed into a single level programming problem, which can be simplified by some rule. So we can search the o... By applying Kuhn-Tucker condition the quadratic bilevel programming, a class of bilevel programming, is transformed into a single level programming problem, which can be simplified by some rule. So we can search the optimal solution in the feasible region, hence reduce greatly the searching space. Numerical experiments on several literature problems show that the new algorithm is both feasible and effective in practice. 展开更多
关键词 quadratic bilevel programming genetic algorithm optimal solution
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Approach for uncertain multi-objective programming problems with correlated objective functions under C_(EV) criterion 被引量:2
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作者 MENG Xiangfei WANG Ying +2 位作者 LI Chao WANG Xiaoyang LYU Maolong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第6期1197-1208,共12页
An uncertain multi-objective programming problem is a special type of mathematical multi-objective programming involving uncertain variables. This type of problem is important because there are several uncertain varia... An uncertain multi-objective programming problem is a special type of mathematical multi-objective programming involving uncertain variables. This type of problem is important because there are several uncertain variables in real-world problems.Therefore, research on the uncertain multi-objective programming problem is highly relevant, particularly those problems whose objective functions are correlated. In this paper, an approach that solves an uncertain multi-objective programming problem under the expected-variance value criterion is proposed. First, we define the basic framework of the approach and review concepts such as a Pareto efficient solution and expected-variance value criterion using an order relation between various uncertain variables.Second, the uncertain multi-objective problem is converted into an uncertain single-objective programming problem via a linear weighted method or ideal point method. Then the problem is transformed into a deterministic single objective programming problem under the expected-variance value criterion. Third, four lemmas and two theorems are proved to illustrate that the optimal solution of the deterministic single-objective programming problem is an efficient solution to the original uncertainty problem. Finally, two numerical examples are presented to validate the effectiveness of the proposed approach. 展开更多
关键词 uncertainty theory uncertain multi-objective programming expected-variance value criterion
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MIXED ENERGY METHOD FOR SOLUTION OF QUADRATIC PROGRAMMING PROBLEMS AND ELASTIC-PLASTIC ANALYSIS OF TRUSS STRUCTURES 被引量:1
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作者 Zhong Wanxie Zhang Hongwu 《Acta Mechanica Solida Sinica》 SCIE EI 2002年第1期1-8,共8页
A new algorithm for the solution of quadratic programming problemsis put forward in terms of the mixed energy theory and is furtherused for the incremental solution of elastic-plastic trussstructures. The method propo... A new algorithm for the solution of quadratic programming problemsis put forward in terms of the mixed energy theory and is furtherused for the incremental solution of elastic-plastic trussstructures. The method proposed is different from the traditionalone, for which the unknown variables are selected just in one classsuch as displacements or stresses. The present method selects thevariables in the mixed form with both displacement and stress. As themethod is established in the hybrid space, the information found inthe previous incremental step can be used for the solution of thepresent step, making the algorithm highly effi- cient in thenumerical solution process of quadratic programming problems. Theresults obtained in the exm- ples of the elastic-plastic solution ofthe truss structures verify what has been predicted in thetheoretical anal- ysis. 展开更多
关键词 elastic-plastic analysis mixed energy method quadratic programming problem
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An Interval Maximum Entropy Method for Quadratic Programming Problem 被引量:3
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作者 RUI Wen-juan CAO De-xin SONG Xie-wu 《Journal of China University of Mining and Technology》 2005年第4期379-383,共5页
With the idea of maximum entropy function and penalty function methods, we transform the quadratic programming problem into an unconstrained differentiable optimization problem, discuss the interval extension of the m... With the idea of maximum entropy function and penalty function methods, we transform the quadratic programming problem into an unconstrained differentiable optimization problem, discuss the interval extension of the maximum entropy function, provide the region deletion test rules and design an interval maximum entropy algorithm for quadratic programming problem. The convergence of the method is proved and numerical results are presented. Both theoretical and numerical results show that the method is reliable and efficient. 展开更多
关键词 quadratic programming interval algorithm penalty function maximum entropy function
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Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints 被引量:1
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作者 Ruopeng Wang Hong Shi +1 位作者 Kai Ruan Xiangyu Gao 《Applied Mathematics》 2014年第2期256-262,共7页
The present paper is devoted to a novel smoothing function method for convex quadratic programming problem with mixed constrains, which has important application in mechanics and engineering science. The problem is re... The present paper is devoted to a novel smoothing function method for convex quadratic programming problem with mixed constrains, which has important application in mechanics and engineering science. The problem is reformulated as a system of non-smooth equations, and then a smoothing function for the system of non-smooth equations is proposed. The condition of convergences of this iteration algorithm is given. Theory analysis and primary numerical results illustrate that this method is feasible and effective. 展开更多
关键词 FIXED-POINT ITERATION CONVEX quadratic programming Problem Convergence SMOOTHING Function
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A New Heuristic for the Convex Quadratic Programming Problem 被引量:1
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作者 Elias Munapo Santosh Kumar 《American Journal of Operations Research》 2015年第5期373-383,共11页
This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual Karush-Kuhn-Tucker conditions are used but in this case a linear objective function is also formulated from the set ... This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual Karush-Kuhn-Tucker conditions are used but in this case a linear objective function is also formulated from the set of linear equations and complementarity slackness conditions. An unboundedness challenge arises in the proposed formulation and this challenge is alleviated by construction of an additional constraint. The formulated linear programming problem can be solved efficiently by the available simplex or interior point algorithms. There is no restricted base entry in this new formulation. Some computational experiments were carried out and results are provided. 展开更多
关键词 CONVEX quadratic programming Linear programming Karush-Kuhn-Tucker Conditions SIMPLEX METHOD Interior Point METHOD
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New approach for uncertain random multi-objective programming problems based on C_(ESD) criterion 被引量:1
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作者 SUN Yun WANG Ying +2 位作者 MENG Xiangfei FU Chaoqi LUO Chengkun 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第3期619-630,共12页
To overcome the defects that the traditional ap-proach for multi-objective programming under uncertain ran-dom environment(URMOP)neglects the randomness and uncer-tainty of the problem and the volatility of the result... To overcome the defects that the traditional ap-proach for multi-objective programming under uncertain ran-dom environment(URMOP)neglects the randomness and uncer-tainty of the problem and the volatility of the results,a new ap-proach is proposed based on expected value-standard devi-ation value criterion(C_(ESD) criterion).Firstly,the effective solution to the URMOP problem is defined;then,by applying sequence relationship between the uncertain random variables,the UR-MOP problem is transformed into a single-objective program-ming(SOP)under uncertain random environment(URSOP),which are transformed into a deterministic counterpart based on the C_(ESD) criterion.Then the validity of the new approach is proved that the optimal solution to the SOP problem is also effi-cient for the URMOP problem;finally,a numerical example and a case application are presented to show the effectiveness of the new approach. 展开更多
关键词 chance theory independent-uncertain random multi-objective programming expected value-standard derivation value criterion(C_(ESD)criterion)
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A PREDICTOR-CORRECTOR INTERIOR-POINT ALGORITHM FOR CONVEX QUADRATIC PROGRAMMING
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作者 Liang Ximing(梁昔明) +1 位作者 Qian Jixin(钱积新) 《Numerical Mathematics A Journal of Chinese Universities(English Series)》 SCIE 2002年第1期52-62,共11页
The simplified Newton method, at the expense of fast convergence, reduces the work required by Newton method by reusing the initial Jacobian matrix. The composite Newton method attempts to balance the trade-off betwee... The simplified Newton method, at the expense of fast convergence, reduces the work required by Newton method by reusing the initial Jacobian matrix. The composite Newton method attempts to balance the trade-off between expense and fast convergence by composing one Newton step with one simplified Newton step. Recently, Mehrotra suggested a predictor-corrector variant of primal-dual interior point method for linear programming. It is currently the interiorpoint method of the choice for linear programming. In this work we propose a predictor-corrector interior-point algorithm for convex quadratic programming. It is proved that the algorithm is equivalent to a level-1 perturbed composite Newton method. Computations in the algorithm do not require that the initial primal and dual points be feasible. Numerical experiments are made. 展开更多
关键词 CONVEX quadratic programming INTERIOR-POINT methods PREDICTOR-CORRECTOR algorithms NUMERICAL experiments.
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Successive quadratic programming multiuser detector
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作者 Mu Xuewen Zhang Yaling Liu Sanyang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第1期8-13,共6页
Based on the semidefinite programming relaxation of the CDMA maximum likelihood multiuser detection problem, a detection strategy by the successive quadratic programming algorithm is presented. Coupled with the random... Based on the semidefinite programming relaxation of the CDMA maximum likelihood multiuser detection problem, a detection strategy by the successive quadratic programming algorithm is presented. Coupled with the randomized cut generation scheme, the suboptimal solution of the multiuser detection problem in obtained. Compared to the interior point methods previously reported based on semidefmite programming, simulations demonstrate that the successive quadratic programming algorithm often yields the similar BER performances of the multiuser detection problem. But the average CPU time of this approach is significantly reduced. 展开更多
关键词 Code division multiple access Multiuser detection Semidefinite programming Successive quadratic programming.
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