Descending Dimension Algorithmfor Quadratic Programming Problem

This paper deals with the linear equations algorithm for quadratic programming problems with equality constraints.In this paper the optimality conditions were used for programming problem with equality constraints and then a linear equation was established. Finally the solution of these leads to optimal solution of quadratic programming problems.     

AN APPROACH TO SOLVING QUADRATIC PROGRAMMING AND ITS APPLICATION TO SECURE ECONOMIC DISPATCH

Based on the selaxaticn t echnique, a new approach to solving quadratic programming is presented in this paper. The idea of parametric programming is introduced in the process of solving the problem,and the optimal solution can be obtained through a finite numfer of search iterations. The features of the proposed method are few regurements for the initial values and little computation. It can also be used to solve the parametric quadratic programming. As an example of application, it is applied to solve a real power secure economic dispatch problem in electric power systems,and its calculation results are given.     

The Approximate Method of Quadratic Function With Mixed Constraint

A reduced method to solve the problem with equality constraints is given. Based on the reference we use nonlinear equality constraints, the approximate algorithm is obtained. The nonlinear programming of quadratic function with equality and unequality constraints is discussed by Wang kairong. We transform unequality constraints into equality constraints by add to relaxation variable, the quadratic programming is obtained by linear approximation, and approximate calculation is done by means of reduced method. The result of numerical calculation shows the method is feasible.     

Descending Dimension Algorithm for Convex Nonlinear Programming Problem with Equality Constraints

This paper deals with the nonlinear system of equations algorithm for convex nonlinear programming problems with equality constraints.We use the optimatily conditions for programming problem with equality constraints and then estabish a nonlinear system of equations.Finally we solve these to get optimal solution of nonlinear programming problems.     

A New Heuristic Evolutionary Programming and Its Application in Solution of the Optimal Power Flow

A new algorithm,based on the combination of the evolutionary programming with the traditional gradient adjustment technique,is presented for solving the optimal power flow problem which describes some technical problems(representations of candidate solutions,evaluation function,mutation operator).Its efficiency is higher than that of general evolutionary programming.     

The Generalized Conjugate Direction Method for Constrained Optimization A Geometrical Approech

The conjugate direction method for solving the unconstrained optimization problem is extended to solving the constrained optimization problem by method of differential geomtry.By inducing a new class of affine connections on a constrained sub-manifold, the primary constrched optilnhation problem is converted to a unconstrained local quadratic programming problem.Based on the definition and construction of a new class of generalized conjugate directions, it isproved that optimum value of the primary constrained optimization problem must be located on thegeodesic line which is formed by the conjugate directions mentioned above and can be reached withinfinite searching step. Therefore a new curve search algorithm with generalized conjugate directions isput forward.     

TRUST REGION METHOD FOR UNCONSTRAINED OPTIMIZATION

A new trust region algorithm is proposed for solving unconstrained optimization problems. According to the quadratic approximate model of the original optimization problem,the trust region algorithm uses directions,a convex combination of the quasi-newton direction and the steepest descent direction. This algorithm with new strategy is analyzed and the global and local quadratic convergent theorems are proved. At last,the implementation and computational results of the algorithm are demonstrated.     

Model and algorithm of transmission congestion management basedon matchmaking tradeoff competition mechanism settlement

A new congestion management model based on high low settlement is proposed for the electricity market. The model combines the transaction mechanism and congestion management to eliminate congestion in branches with the minimum equivalent increase in the system regulating fee. The equality constrains are the branch overloads, the generator sensitivities, and the corresponding adjustments, respectively. By introducing the Lagrange multiplier and a relaxation factor, the nonlinear programming problem with constraints can be translated into an unconstrained nonlinear programming problem. The regulating values of the generators thus can be obtained. The proposed algorithm is verified by a 6 bus system.     

Optimality Conditions for Nonsmooth Extremum Problems in Topological Vector Spaces

Some new concepts of coneD_s convexity,coneD-s quasiconvexity,cone D-s pseudoconvexity,s right derivative of vector value mapping are proposed;and their related properties are discussed;the optimality necessary conditions and sufficient conditions for constrained extremum problem(VP)involving in cone D-s convex mapping are extablished;the relation between local optimal solution and global optimal solution;as well as the relation between weakly efficient solution and efficient solution for (VP) are derived;the corresponding results generalize the related results of classic convex programming.     

Distributed Cutting Stock System Based on Heuristic Search and Knapsack Algorithm

A approximate algorithm is presented by which satisfactory results of two dimensional optimal layout belonged to NP complete problems can be obtained efficiently and rapidly. The algorithm integrated with widespread of computer network has been applied to the distributed cutting stock system Adopting Heuristic search and Knapsack algorithm, the algorithm makes each layout optimal locally and obtained the approximate optimal solution. It is compared with other two approximate algorithms and pointed out their shortcomings. In the end of the article a layout example was presented.     

Hybrid Intelligent Method for Dynamic Reactive Power Optimization

In dynamic reactive power optimization problem(DRPO), action number constraints of discrete variables should be considered.By integrating immune genetic algorithm(IGA) and nonlinear interior point method(NIPM), a hybrid method for DRPO is proposed.First,the original DRPO problem is converted to a continuous optimization problem by relaxing the discrete variables,and the solution is obtained by NIPM.Then,according to the feature of control variables,the original DRPO problem is decomposed into a continuous optimization sub-problem and a discrete optimization sub-problem.The discrete optimization sub-problem is solved by IGA,and the continuous one is solved by NIPM.By solving the two sub-problems alternately,the optimal solution of the DRPO can be obtained.The proposed hybrid method combines advantages of IGA and NIPM,and finds the approximate optimal solution of DRPO.Numerical simulations on the IEEE 14 bus system illustrate that the proposed hybrid method is effective.     

AUTOMATIC CONTINGENCY SELECTION AND RANKING BY NETWORK PROGRAMMING APPROACH

This paper presents a new approach ,to the automatic contingency selection and ranking by the network flow programming (NFP). A complex cost optimisation model based on economy and security, and several simplified models are proposed in the paper. The performance index is the total load curtailment or its weighted value. All the solution algorithms are OKA. The model and its algorithm is tested on IEEE 30-Bus System and the encouraging results are obtained.     

Hybrid Genetic Algorithm Based on Novel Adaptive Penalty Function

The authors introduce a sort of novel adaptive penalty gene, transform the constrained problem into unconstrained problems. An solution is given for this unconstrained problem with genetic algorithm, and then it is used as initial values for the constrained variable metric method to get precise solution. The numerical experiments illustrate that this hybrid genetic algorithm is more efficient than the genetic algorithm, and at most situations globally optimal solution can be gotten.     

Optimization Model of Non-rhythm Flow Process and the Dynamic Programming Algorithm

The flowing sequence has important effect to the flow ste Pdistance and the period of non-rhythm flowing construction,algorithmic research of ordering and step distance calculation are always difficult point of non-rhythm flowing construction optimizes studying.An optimization model of non-rhythm flow process is founded,and a common method for confirming the length of flow step was put forward.In order to find the solution of the optimization model conveniently,the optimization problem is transformed to shortest path problem skillfully.A dynamic programming algorithm is given to make the construction project period as shorter as possible,to reduce cost and improve economic efficiency.     

Distribution Network Structure Planning Based on Multi-population Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem, which is difficult to solve properly by using traditional optimization methods. The authors put forward Multiple Population Immune Genetic Algorithm (MPIGA)for optimal planning of distribution network structure, and do optimal search to different aspects of optimization goals. During the genetic evolution process, biologic immune mechanism is introduced to do some immune operator operation on chromosomes of each population, which can interact mutually by the shift of excellent units. By this way, it can effectively prevent population retrogression, promote diversity and the whole optimal searching ability of genetic algorithm. In order to minimize network annual expenditure, a mathematic model is established. The optimal solution is obtained by this algorithm, which has been illustrated effectively by specific examples at the same time.     

THE APPLICATION OF NETWORK PROGRAMMING METHOD ON THE SHORT TERM OPTIMAL SCHEDULING FOR CASCADED HYDROPOWER STATIONS

The problem of the short term economic scheduling for cascaded hydropower stations is discussed with the network programming method. A new network model is built to dispatch the load to each unit when the unit commitment is determined. An algorithm of the minimal cost maximal flow is also discussed using the model and the algorithm to the Longxi River Cascaded Hydropower Stations, the computational result on the microcomputer VAX II shows that the model and the algorithm are correct and applicable.     

EXISTENCE OF A BASIC OPTIMAL SOLUTION FOR LINEAR VECTOR EXTREME VALUE PROBBEM

In this paper, the concept of basic for linear vector extreme value problem is introduced in the partially ordered vector space. Some properties and results of the linear programming are generalized. And the existaence therom of basic optimal solution is proved.     

Reliability evaluation algorithm for complex electrical distribution networks using the storage structure of adjacency multilist

A section algorithm of reliability evaluation for complex medium voltage Electrical Distribution Networks (EDNs) using adjacency multilist (AM) is proposed. The constructing method for AM is introduced. The AM can be used to store the structure data of EDNs and to solve the problem of space & time complexity. A new power flow algorithm of backward / forward sweep is proposed and a fast algorithm of forming sections in distribution network is put forward. The proposed algorithm makes a perfect combination of the power flow algorithm and the section algorithm of reliability evaluation, which makes efforts to decrease the work of programming and saves the computing time. Applying the proposed algorithm in RBTS-BUS6 system and actual EDNs, the reliability assessment results show that the algorithm has an advantage of saving time and possesses efficiency in engineering practicality.     

On a New Lower Order Exact Penalty Function

For the inequality constrained nonlinear programming problem, the antnors propose a new lower order penalty function, which combines the classical l1 penalty function and the lower order exact penalty function introduced in thoy some papers, and then illustrate that it has the merits of the two penalty functions. In additional, we propose a solution method for solving the inequality constrained nonlinear programming problem and prove its global convergence.     

响应面优化棉子饼粕中棉酚的提取条件

 采用响应曲面法的Box-Behnken模式,以盐酸和80%乙醇混合溶液作为提取液浸提棉子饼粕中棉酚工艺条件进行了研究,并建立提取棉酚的二次多项数学模型,探讨了主要因素的影响效应及其交互作用。采用响应曲面法优化得出的最佳工艺条件为：浸提温度60℃,提取液用量为26 mL·g^-1,盐酸浓度为1 mol·L^-1,浸提时间为3.6 h,提取次数1次时,提取量为8.80 mg·g^-1。