The Application of Furry Decision for Generation Expansion Planning

Fuzzy decision was applied to the generation expansion planning and a method of fuzzy decision of generation expansion planning has been presented in this paper.     

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.     

Avoiding Obstacle Planning for Robots on Molecular Optimization Algorithm

Interest in DNA computing has increased overwhelmingly since Adleman successfully demonstrated its capability to solve Hamiltonian Path Problem. This article introduces the improving method in virtue of the biological thery of DNA technology, a new molecular algorithm is advanced. After a numerical simulation, the result shows that it avoids the prematurely and lower convergent speed of the classic genetic algorithm, and inherits global search capability, the validity and the speed of the genetic algorithm have been increased. The best result can be obtained in few iterative times. It is fit for solving path planning problem.     

A Muti-Objective Network Planning Model for Project

Based on the network planning model developed by the author for an overhaul project of a rolling mill production line in a heavy steel plant, an new multiobjective network planning model is proposed in this paper. The formulations of network time parameters are derived. The optimization problem of multiobjective network planning is also discussed. And it has been found out that the fractional single-objctive network is only one of the cases in this model.     

Dynamic Route Guidance System Based on Genetic Algorithm

The study on Dynamic Route Guidance System (DRGS) is an important research in the field of Intelligent Transportation System(ITS),which guide the behaviors of travelers by providing them with optimal route based on real-time traffic information. As a result the travel time can be saved and the traffic congestion can be avoided. The route guidance algorithm can compute the best route between the begin point and destination. The globe near best property and real-time property must be considered , the Genetic Algorithm have qualifications for globe optimal and parallel algorithm. Genetic algorithm(GA),for solving the shortest route,is proposed in this thesis?The ordered real code rule,crossover,mutation are given. The efficiency of the GA is proved through an example.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

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.     

Investigations of Distribution System Planning of Loop Configurations Using a Genetic Algorithm

The distribution system planning is performed with a loop configuration constraint from scratch.With Evolutionary Algorithm,a sample distribution network is designed with a loop configuration,in which the system is operated as radial configuration.It firstly introduces the mathematical model for distribution network planning,then the application of Evolutionary Algorithm for the planning of distribution network.By using the theory mentioned above, Visual C++ is applied to develop the distribution network optimization software.Finally with the optimization process of 17 nodes system being showed,the presented algorithm's utility and validity is verified.     

Fast Algorithm About Unit Commitment Based on Revised BP Artificial Neural Network and Dynamic Search

In order to reduce the operation cost and optimize the unit commitment,the fast algorithm about unit commitment based on revised BP ANN(Artificial Neural Network) and dynamic search is discussed.The BP ANN is trained with Levenberg-Marquardt algorithm,which aiming at its drawback of the storage of some matrices that can be quite large for certain problems,and a revised algorithm is presented.The BP ANN is used to generate a pre-schedule according to the input load profile.Then the dynamic search is performed some stages where the commitment states of some of the units are not certain.The experimental results indicate that the proposed algorithm can reduce the execution time and memory space without degrading the quality of the generation schedule.     

Algorithm to Transform Dynamic Causality Diagram Into Belief Network

The Dynamic Causality Diagram methodology is a new probabilistic reasoning model based on Belief Network. To some extent, it is similar to the Belief Network in structure. So that knowledge from one can be transformed into the other on some conditions. To begin with, this paper discusses the similarities and differences between them, and finally presents a transformation algorithm from Dynamic Causality Diagram into Belief Network. The algorithm is composed of two parts: a mapping algorithm of structure and a generating algorithm of conditional probability tables.     

Study on ES Based Generation System Planning

Based on the analysis of expert experience on generation system planning(GPS), the theory of knowledge based method is introduced into GPS to express the constraints of engineering(viz. Expert experience of engineering), and to discard abundant improper program during the earlier stage of GPS. In this situation, the difficulty degree of optimizing calculation in the later stage of GPS is lessened. And then, integrating expert system with production simulation in a method of GPS is proposed and is verified with an example. The results show that the method presented is effective.     

Investment Model for Expansion Planning of Electric Generating Systems under Uncertainty

In this paper, traditional investment model for expansion planning of electric generating system is modified, the investment model for expansion planning of electric generating system under uncertainty is modeled and the method of calculating option value of waiting is discussed.     

Improvement Algorithm of Generation Cost Based on Reliability

This paper discusses the influenced manner of reliability on bidding, and establishes the direct functional relationship among reliability, generation cost and electricity price in different risk of power generation. In this function model, the generation cost and the price could reflect the current reliability of equipment in a dynamic way. The generation risk is also considered in competitive bidding. The bidding strategy based on this model helps the power plant acquire the optimal benefit.     

Dynamic Finite Element Model Updating of Prestressed Concrete Continuous Girder Bridge Based on Real-Coded Accelerating Genetic Algorithm

The dynamic finite element model (FEM) of a prestressed concrete continuous girder bridge (PCCGB), named Zhangjiagang river main bridge, was established and updated based on the results of field ambient modal testing using real-coded accelerating genetic algorithm (RAGA), which objective function was defined based on frequency index and correlation coefficient index for evaluating the updated FEM. The dynamic FEM of the bridge was updated based on seven experimental modal parameters. The prediction ability of the updated FEM were evaluated based on three experimental modal parameters. The updated results and prediction ability of updated FEMs indicated that they can reflect adequately the dynamic characteristics of actual PCCGB by using the above objective function and RAGA.     

A Land Use Model for Urban Rail Station Area Planning Based on TOD Strategy

Transit oriented development (TOD) presents a sustainable urban development strategy by creating an efficient integration of land use and public transit. A TOD planning model for the land use of urban rail station area was explored by means of a multiple objective mathematical programming model. Three objectives were considered: encouraging transit system volume, promoting livable communities, and balancing land use. The model can easily be solved by transforming it into a linear multi programming problem. The Xujiahui rail rapid transit station area in Shanghai is chosen as case study to illustrate the model application and planning results. The result indicates that the model would be efficient in practice.     

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.     

Loads Equalization Based on Optimization Principle and the Hierarchical Model for Distribution Networks

Loss reduction is important for distribution networks and it is available to reduce loss by loads equalization. With increasing numbers of vertexes in distribution networks, compounding of loads are rapid increasing. It is hard to achieve the global optimization for load balancing by traditional model of distribution networks. Base on analyzing character of loads equalization for distribution networks, this paper provides a new method which conjugate the optimization principle and the hierarchical model of the distribution networks, can transfer the optimization issues into multi stage decision making problems,and can also achieve the optimization equalization of the distribution networks loads.     

水稻叶色变化动态的模拟模型研究

定量描述叶片颜色变化的动态过程是植物生长数字化和可视化的重要内容。本研究通过对不同水稻品种和不同水氮处理条件下主茎和分蘖不同叶位叶色变化过程的连续观测和定量分析，构建了水稻叶片颜色随生长度日变化的动态模拟模型。水稻叶片颜色变化的基本过程可以用3个阶段的SPAD值分别表达，第一阶段为基于幂函数的伸长期，叶色逐渐增强，第二阶段为相对稳定的功能期，叶色基本不变，第三阶段为基于二次曲线的衰老期，叶色逐渐减弱；并基于二次曲线方程分别描述了叶片含氮量和含水量对叶色变化过程的调控效应。在此基础上，进一步建立了叶片SPAD值与叶色组分（RGB）值的关系模型。利用独立的水稻田间试验资料对所建模型进行了测试和检验，显示主茎不同叶位叶色变化3个阶段模拟值的均方根差分别为2.58、3.69和3.82，4个分蘖不同叶位叶色变化模拟值的均方根差分别为4.65、4.39、3.51和4.25；SPAD值与叶色组分间模拟值的均方根差分别为2.98和3.25。表明本模型可较好地模拟不同生长条件下水稻不同茎蘖上不同叶位叶色的动态变化过程，从而为实现水稻生长系统的数字化模拟和可视化显示奠定了基础。     

Bilevel Programming Model and Solution Algorithm for the Supplier Selection in Automobile Components

Focusing on the characteristics of automobile components industry, such as long-term supplier selection, large number of suppliers, various assessment index, complicated processes, and extremely strict assessment requirements, an improved supplier selection bilevel programming model for automobile components industry is established. With this model, the authors analyzed selected objectives from viewpoints of both suppliers and purchasers, assessed several selectied factors with upper and lower layer objective functions, and produced a optimal supplier selection method to achieve minimum purchasing costs. This model takes several constraints, such as technology, quality, quoted price, supply capacity and services of suppliers, into consideration, which makes the model very practical. A genetic-algorithms-based calculation method is designed, and the model is validated through a case study. Both the model and the method provide valuable support to supplier selection in the automobile components industry.