Search

In this work, two types of optimization problems which are crucially related to batch reactor operation are considered. First problem is to maximize the conversion and second problem is to minimize the batch time. Both problems are solved using sequential quadratic programming (SQP) available in Aspen Plus. The manipulated variables i.e. reactor temperature and amount of palm oil are optimized simultaneously based on the specified objective function and equality constraint. Effect of intervals for both optimization problems are also evaluated in this paper. The results show that in maximizing conversion, the number of intervals did not significantly affect the amount of conversion. Meanwhile in minimizing batch time, the introduction of intervals was positively reduced the reactor temperature but negatively minimize the batch time.

The fast network restoration is required to restore the Shipboard power system (SPS) to near pre-fault condition for proper functioning. This paper proposed an improved Particle Swarm Optimization for restoration of shipboard power system. Firstly, we proposed an improvement strategy of S-Curve Decreasing Inertia Weight. Secondly, the feedback mechanism was introduced to improve the algorithm rate of convergence. Particle swarm optimization algorithm enables to find the optimal combination of loads that can be supplied after the occurrence of the fault, considering the priorities of the loads and the constraint of balance between the total load and total generation. The proposed method is applied to a naval shipboard power system model.

This paper considers a scheduling problem of two parallel machines with a resumable availability constraint. The objective is to minimize the makespan. The problem is NP-hard in the ordinary sense. Therefore, we need to find an approximate solution that fulfills the required error bound. To get a better approximation solution in a polynomial running time, we propose a fully polynomial-time approximation scheme (FPTAS) by trimming states space.

Study on solar thermal technology along with its radiation, collection, storage sub-models are full of illuminations in many similar phenomena, so this paper analyzes dimensions in its radiation, collection processes, and founds dimensionless model for these processes, and also figures out their similarity laws, and then extends its radiation, collection theory and technology to fire evolution process, and generalizes fire-protection idea and method: besides directly extinguishing fire by cool water and other constraint agents, we try to collect and transfer fire radiation, as the result, indirectly extinguish fire. This generalization is expected to many brand-new extinguishing fire technologies in the future.

The extradosed cable-stayed bridge is a new type of bridge developed in recent year. The main girder bears most of the load with its great stiffness, while the cable tension can improve the force state of the girder. So it is really necessary to optimize the cable force to determine the internal force of extradosed cable-stayed bridge under the rational completion state. But the optimization methods commonly used are based on the cable-stayed bridge and not entirely suit for the extradosed cable-stayed bridge. The paper puts forward a new optimization method, which includes applying the unknown coefficient functions aided by MIDAS/CIVIL, taking the reasonable feasible range of dead moment solved by stress balanced method as the constraint condition, making the square of unknown coefficients as objective function, and solving the cable force based on the effect matrix method thus to determine the cable force in reasonably completion state. This new method is verified with favorable effect, the internal force of this structure appear significant improvement. And finally, the results show better cable force obtained under the method in this paper compared with the cable force under other constraint conditions and objective functions.

A sequence planning algorithm based on multiple-constraint model was proposed to solve the problems in the bending process of complex workpiece. By employing a heuristic search based A* algorithm, the sequence planning was converted to a generalized shortest path problem, and then a multiple-constraint model which includes the factors of bending feasibility, dimensional accuracy and processing efficiency was introduced to optimize the search process. A bend sequence planning system has been realized based on this algorithm. The testing results of the system indicate that the algorithm is efficient and stability, and the planning time of complex bending workpiece was reduced effectively, especially for the workpieces which don’t have the valid bending process.

Due to different travel experiences, travel attitude varies from people of different levels of familiarity with urban route network. Expected utility theory (EUT) is usually used to describe travelers’ route choice behavior. But there is huge discrepancy between reality and the results under the condition with network uncertainty when the cumulative prospect theory (CPT) is more attractive to describe the travelers’ route choice behavior. Based on CPT this study designs scenarios at different levels of familiarity with urban road network, analyzes route choice behavior in all scenarios and conclude travelers’ behavior characteristics compared with reality investigation results. It shows that CPT is really more powerful to describe the travelers’ behavior under risk and people of high familiarity level are more relied on constraint time and tend to take a risk for more gain.

In view of the disadvantage existing in stochastic programming and fuzzy programming that in the process of modeling of wind power both of them need a huge amount of historical data information to establish precise model, and the advantage of interval planning that it only need to know the upper and lower bounds of the variable in the uncertainty modeling and interval variables contains more information than real variables, this paper puts forward the interval model of the wind power, and use the interval possible degree to deal with the interval constraint conditions. At the same time, this paper adopted the chaotic particle swarm optimization algorithm based on logic from the map to solve the model. Finally, the paper proved the accuracy and effectiveness of the model and algorithm by an example.

The principle and cost analysis of Constraint-Based Space-Time Adaptive Monopulse (C-STAM) are given. Based on the idea of cognitive radar, a novel Knowledge-Aided Constraint-Based Space-Time Adaptive Monopulse (KA-C-STAM) is proposed. With the knowledge given by a tracking filter in data processing, the KA-C-STAM improves the performance of angle estimation. Numerical examples verify the validity of the novel method.

This paper presents a theoretical line loss calculation of distribution network containing an uncertainty power of wind turbine. First, this paper establishes the theoretical line loss mathematical model considering wind turbine power constraint within the sampling period. Then this paper gets multi group wind turbine output data satisfied the power constraints through Monte Carlo simulation. By combining with the first power coefficient method and Monte Carlo simulation technique, this paper also generates multi groups load pseudo measurement test of non real time. By combining the real-time measurement of power flow calculation, a group of simulated data with minimum error between the power flow results and the real time measurement are selected. Finally based on the selected pseudo measurement, the theoretical line loss within the given time period based on periodic accumulative calculation of real-time measurement are calculated. 14 nodes example is given to verify the accuracy and practicality of the algorithm.

Materialized view is an important topic in data warehouse research, and also affects the query efficiency and maintenance cost. The disk-space view-selection problem is to select a set of materialized views for the purpose of minimizing the total query processing cost and the total maintenance cost. In this paper we introduce evolutionary algorithm using stochastic ranking algorithm, which can enable materialized view selection under disk-space constraint. The algorithm improve the stochastic ranking algorithm, which can find a near-optimal feasible solution. This paper use the algorithm in Police data warehouse.

Recent approaches for reconstructing 3D scenes from image collections only produce single scene models. To build a unified scene model that contains multiple subsets, we present a novel method for registration of 3D scene reconstructions in different scales. It first normalizes the scales of the models building on similarity reconstruction by the constraint of the 3D position of shared cameras. Then we use Cayley transform to fit the matrix of coordinates transformation for the models in normalization scales. The experimental results show the effectiveness and scalability of the proposed approach.

A method of multiplier is presented for solving optimization problems. For large-scale constraint problems, combining the active set strategy, we use the aggregate function to approximate the max-value function. Only a few of functions are involved at each iteration, so the computation for gradient is significantly reduced. The numerical results show that the method is effective.

This paper proposes a new path planning algorithm based on the CNN model. The path planning problem is completed with the dynamics of CNN by establishing a relationship between path control points and CNN cells. Based on the analysis of one dimensional space of CNN algorithm, a CNN equation is constructed and the path updating algorithm under the curvature constraint is obtained, then the stability of the algorithm is discussed. Path planning simulation based on two-dimensional space shows that this algorithm can avoid re-planning or falling into the local minimum, which means it can be successfully used in the path planning and maintenance of robots on the ground in dynamic environment.

This paper addresses the observer design for simultaneously estimating the state and input of a class of impulsive systems whose nonlinear terms satisfy an incremental quadratic constraint. By employing Lyapunov theory, sufficient conditions for asymptotical and exponential estimation convergence are derived. Gain matrices of the proposed observer can be obtained by solving linear matrix inequalities (LMIs).

Based on the theory of unban carbon sink , search it according to actual situation of the study area and related research results, select the most important carbon sink factor which influenced ecological environment and other influences, take them as the effects the constraint conditions of urban ecological space, calculate kinds of carbon sink data. Endow different weight value according to their importance. The factors would be the mutual superposition based on the spatial analysis of GIS, form the ecological support spatial pattern with natural elements. The whole ecological network is constructed of source region, eco-corridors and ecological node with the space connectivity. At the end, optimize the urban ecological spatial pattern in the level of urban carbon sink distribution, help urban to become more perfect on planning and development.

This paper is mainly discussed in areas under a unified multi-domain framework, the unified constraint expression of optimization simulation model and critical theory in the process of solving. Establish the multi-domain optimization simulation model of complex product, study the complex coupling between multi-domain constraint models, analyze the parameters sensitivity of unified constraint expression model and reduce the restraint scale. Using the principle of global satisfaction as far as possible, to achieve coordination of multi-domain constraints based on the component level, solving the Large-scale multi-domain unified optimization simulation model with the homotopy iteration method.

Based on the theories of density interpolation schemes for structural topology optimization,introduced the method of moving asymptotes to the theories of RAMP.With the structural volume as the constraint,the method of moving asymptotes based on the theories of RAMP to solve the problem of minimize structure compliance.The correctness and validity of the method were verified by a case.

This paper is mainly discussed the establishment of the unified constraint expression of simulation optimization model. Express all kinds of element constraints with unified physical mathematical mapping mechanism, uniform the model representation of product components in each domain and establish the unified expression model, in order to facilitate the follow-up simulation solution of multi-domain constraint system.

The mechanical models with and without thimble constraints for the turning work-piece are built respectively, applying ABAQUS software to analyze the modes of work-piece, then the law of the influence that different turning depth on the bending modes of work-piece is obtained. The study indicates that each-order natural frequency increase gradually in linear form for the work-piece without thimble constraint, while for the work-piece with thimble constraint, the natural frequency of the first four orders decrease linearly with the increase in the turning depth, but the change of high order frequency is relatively complicated.

A design method for ground-coupled heat pump (GCHP) systems with specific constraint conditions is proposed. The total borehole number, borehole depth, borehole space and average velocity of fluid in the U-tube are considered as variables in the optimization problem. The optimization problem of four variables is transformed into that of single decision variable. A case study, which includes different schemes for designing GCHP systems of an office building and the corresponding economic analysis, is performed with the aid of simulation software. The result shows that optimal design parameters could be found in an economic optimization problem with specific constraint conditions. Additionally, design parameters may have a notable influence on the energy consumption of circulating pumps. The optimization method in this paper could be utilized by engineering designers for reference.

This paper proposes a method of buzzwords extraction for micro-blogs using buzzwords word-formation features and event correlation. This method includes four important steps. The first step finds out all the candidate words from micro-blog topics by using repeated string searching algorithm. The second step filters the candidate words based on the repeat string properties and language model. The third step extracts the candidate buzzwords through the constraint of words role relationship and special structure model. The last step is to filter the buzzwords according to the words event correlation. The experiments show that the method is accurately and efficiently to extract buzzwords.

At present, most of the domestic train wheel detection is still manual. Existing image detection methods do not fully consider the characteristics of wheel profiles, as the algorithm is very complicated, they do not apply to fast dynamic monitoring. The paper proposes a dynamic image recognition method of train wheels based on contour feature. Firstly, wheel contour curve is extracted using RCD circular arc detection algorithm with constraint condition. Then, after analyzing the wheel contour curves, vector contour is constructed to describe them. At last, images of wheels are rapid recognized, and the recognition is based on identification function. Experimental results show that this method can achieve 95% accuracy when the similarity of complete wheel is set to 0.98 or more. This method can adapt to railway environment and has a certain application value.

Scientific and reasonable signal control would effectively improve the traffic efficiency and safety of roundabout. In this paper, a simplified signal timing method based on the constraint of left-turn queue length was investigated. Taking ZhuQue Roundabout for example, this paper utilized a simulation model based on VISSIM and adopted evaluation index system of capacity, saturation and average vehicle delay. By comparing the results of before and after the new timing, feasibility and effectiveness of the proposed model has been verified.

The theory of plates and shells is not adapted to design thickness for the multi-holes plates in engineering. A new method to quickly optimize the thickness based on the finite element method theory was put forward. The method combined the theory of plate with the finite element method to establish a mathematical model and analyzed the influences of load, constraint and complexity on design error. The practices demonstrated that the proposed design method is effective and feasible.

A new optimization method of pile-anchor support for foundation pit based on BP neural network was been proposed and applied in engineering example. Uniform test can be used to construct study samples efficiently. BP neural network is taken advantage to build a prediction model and predicting results of large number of random samples. Then, according to the constraint condition of optimization criterions, the best optimization result screened out from results. Through an engineering optimization example, it is showed that this method is efficient and with good economic and practical value.

Reliability growth assessment is an important part of the reliability growth management. According to the characteristic that the lifetime of electromechanical product obeys the Weibull distribution, the thesis provides a monotonous constraint model of reliability growth of Weibull distribution, including complete Samples and censored samples. The method proposed in this paper has been verified by actual data, and has good adaptability. The comprehensive evaluation results of MTBF are higher than those got through only utilizing the test data of the last stage.Background Information

Conflict resolution is proposed for BTA boring based on optimization algorithm in this paper, which is capable of finding the bottleneck of value assignment by taking advantages of redundant extensibility in the range of constraint parameters. It can realize the optimum precision index of manufactured component with the minimal loss parameter interval, which is through establishing the relaxation model for parameter range optimization considering strategy of conflict resolution. The potential conflict in technical plan can be detected at the beginning of parameter selection accompanied with the constraint consistency algorithm. The conflict resolution strategy can implement effectively for the range of quantitative parameters. The bottleneck restricting the values can be found by taking the advantages of the redundant expandability of constraint parameters ranges, to realize the optimum processing precision index for components at the lowest loss of parameters ranges. At last, the calculation case verifies the effectiveness of the research methods.

Aiming at measuring path planning, based on inspection MBD (Model Based Definition) models of the measured parts, size and position information of the parts features are generated. Global coordinate equations of the features are established. In measuring process, probe heads should move along the outer normal vector, and the path should be the shortest. Under these constraint condictons, the obstacle avoidance path are created between the probe head starting points and the inspected features origin points. Finally, an example is given to verify the algorithm, which offers a base for the whole path planning considering the change of the probe heads and their direction.

Thermal infrared camouflage refers to a series of camouflage patterns for coping with modern thermal infrared reconnaissance. In order to solve the problems that the subjectivity of traditional evaluation methods on ground thermal infrared camouflage and correlation constraint is not easy to test and so on. The effect factors of thermal infrared camouflage were analyzed, the index system of model of ground thermal infrared camouflage was established, and based on it, the dynamic DEA (data envelopment analysis) model was applied to evaluate the ground thermal infrared camouflage. The example shows that the method in this paper can be applied to compare the DMUs (decision making units) efficiently and it can select the best DMU.

In order to fit in with the demands of the development of electricity market in China, a multi-objective optimization mathematical model is presented to dispatch load within the units, taking economy, environmental protection and quick responsiveness to dispatching commands into consideration at the same time. And take the minimal whole plants power-supply coal cost rate, the minimal pollutant emissions and the minimal load adjusting time as these three objective functions respectively. The four constraint conditions are unit power balance constraint, load bound constraint, ramping constraint and pollution discharge standards constraint. An improved particle swarm optimization algorithm is used to get the Pareto solution set. The optimal solution was obtained by using the method of multi-attribute decision making, through sequencing the solution set by comprehensive evaluation. A case study based on a power plant with 4×600MW units was carried out. The result shows that the method can solve the multi-objective optimal load distribution problem accurately and quickly, and get the good effect in energy conservation and emissions reduction.

This paper studies the near-field beamforming. Based on near-field model, a constraint optimum beamforming algorithm is proposed. The algorithm transforms solving weight value into optimal solution searching, and obtains the optimal weight value by iterative solution. The algorithm can produce optimal beamforming under restricted mainlobe condition. Analogously, it can produce the optimal beam forming under sidelobe constraint. The algorithm can be modified appropriately depending on the desired targets to achieve the desired response control constraints. The algorithm is simple. The simulation results based on discrete uniform linear array show the validity and effectiveness of the method.

This paper proposes a dimensionality reduction mathematical model based on feedback constraint for High-dimensional information. It uses feedback restriction technique to construct dimensionality reduction model for multidimensional product data. The data obtained is with high latitudes, where a large number of data are under components involved standardized restrictions. High-dimensional data participating in operation will increase the complexity of operation, and hence, we need to reduce its dimension. In this paper multi-constrained inverse regression model is adopted to reduce the dimension of cloud resource scheduling data in multi-constrained environments. Experimental results show that the proposed method increases the data coverage rate of high-dimensional data mining by 66%, and has great optimizing effect.

In the paper, we have a study on reconstruction technology from single image, particularly on geometric constraint based methods. We analyze several important geometry constraint relationships in the image and derive corresponding function expression. In this way, the depth of each image point can be gained relatively accurately. With the depth of object points, we fulfilled model reconstruction from a single image. We call the single image reconstruction method as sequential method which need calculate depth of object points one by one. In the experiment, the results prove the visual effect of the algorithm is satisfactory.

The degree-constrained Euclidean Steiner minimal tree problem was discussed based on the Euclidean Steiner minimal tree with each original point being added with a degree constraint. The property of the problem was analyzed and the implementation process of solving the problem by using the ant algorithm was presented.The algorithms is coded in Delphi and run on the Windows XP environment.

This paper proposes a novel unconstrained criterion of blind equalization, which is based on minimizing the difference between two norms of the joint channel-equalizer impulse response. There is no need to impose any constraint on the equalizer coefficients when adjusting. The algorithm is convergent in the sense that a perfect equalization solution is achieved at every local optimum of the function. And we propose a batch algorithm and online-recursive method for implementation. Finally, the reliability, validity and good performance of the proposed algorithm are verified by evaluation of residual ISI through computer simulations.

In order to achieve the reconstruction of existing horizontal railway alignments, automatic identification model and optimization algorithm for existing railway planar feature points are proposed. Firstly total least square method of constraint adjustment quantity is proposed, based on which, automatic identification model is built. Then an evaluation function with the radius of circular curve and the lengths of two transition curves as parameters is presented. Based on the direction acceleration method, a reconstruction optimization algorithm is proposed to optimize this ternary implicit function. The proposed model and algorithm can realize the automatic fitting of measuring points and the optimal localization of planar feature points. Example shows that the reconstruction result is considerably superior to the traditional method and is feasible for the engineering practice.

The model of the electric vehicle charging station location is built in this paper. The objective function is charging station utility maximization, the constraint condition is traffic flow, and simulated annealing algorithm is used to solve this model. The result shows that this model is reasonable to provide the electric vehicle project managers with an optimal or approximate optimal location solution.

Related Vehicle Routing Problem is another form of Vehicle Routing Problem. RVRP also belongs to NP-Hard with a wide range of application areas and major economic value. The research based on single distribution center RVRP with road capacity static constraint, to build a model of single distribution RVRP and propose a kind of chaos genetic algorithm to solve this problem, with experiments verify the feasibility and effectiveness of the algorithm.

In this paper, the usual feedrate control methods are introduced. The characters of them are analyzed. The shortcomings such as the discontinuity of acceleration and jerk in these methods will influence the accuracy of CNC. In order to overcome the weaknesses, a novel feedrate scheme based on fractional power polynomial is proposed. The constraint condition is discussed. The jerk-time curves, acceleration-time curves feedrate-time curves are contrasted. The simulation result shows that this feedrate scheme can fulfill the requirements of high-speed and high-accuracy through the interpolation process.

As one of the important handling equipments in container terminal, the quayside container crane is a major energy consumer. Therefore, the optimization allocation of crane is studied in the paper considering the carbon emission. First, based on the classic method from the economical aspect, an optimization model is established with the goal of minimizing the total loss of vessel waiting for berth and idle berth. Second, a constraint condition for carbon emission of handling unit container by quayside crane is added. Finally, this paper analyses the influence of carbon emission constraint on quay crane allocation. The results show that the allocation optimization model will influence the original plan after considering the carbon emission constraint, and the goal of decreasing carbon emission can be achieved by rearranging quayside crane with the optimization model.

The attitude maneuver duration is an important constraint for an agile Earth observation satellite between its imaging tasks. A method for calculating the attitude maneuver duration from pointing to the last observation target to the next one is proposed. Based on this method, the relationships between the observation times and the attitude changing duration are discussed. The analysis results show that the difference of the observation time and the observation target causes the difference of the attitude maneuver duration between the last and next observation tasks. An attitude maneuver strategy example for an agile satellite in one-orbit strips-jointed observation mode is given. The results of the relationships analysis validate the effectiveness of the attitude maneuver strategy.

The automatic creation of garment parametric computer aided design (PCAD) pattern to special body size is rarely classified and need to be finished with man machine interface at present. This has become a critical and challenging issue to hinder the intelligence process of the garment computer aided design (CAD). In this paper, the basic research aimed at the automatic correction pattern of the special size on the womens jacket CAD system was investigated. The popular special size of women trunk and pattern amendment was selected as research subject, and the relationship between the body characteristics and coat pattern Fig. were set up. The full-scale constraint was developed and the expertise description about womens jacket patterns were finished with the parametric design method based constraint. The mathematic formula and logical definition relation are used to establish relationship with the formed model characteristics of womens jacket patterns. The system then carry and keep the design of womens jacket pattern and the correction logic, and finish the creation and correction of the geometric model to womens jacket pattern. The expertise knowledge of womens jacket pattern correction is applied by the design of method database. The paper performs the basic research and analysis for the rules database creation in the PCAD system, and makes it possible to the research of intelligent womens jacket pattern design system based body size. It will play an active role to transform traditional design concepts and means.

The standard program slicing of different slices is put into the fusion matrix of the optimal fusion to measure the consistent fusion of slices. In the biopsy of the actual fusion process, the slicing techniques with high consistent fusion and balanced fusion distribution are used to reasonably allocate each weight coefficient, and thus the final fusion estimation formula is obtained. We use slice fusion, path conditions, as well as the internal mechanism of software fault trigger and propagation, to construct the test constraint of a fault. It can help to direct high quality test case design and to evaluate the applicability of the adaptive random testing.

In this paper, a new adaptive approach for H_infinity synchronization of a general class of chaotic systems. Based on adaptive control theory and Lyapunov function method, An adaptive controller is constructed, the H_infinity synchronization controller is presented to not only guarantee stable synchronization but also reduce the effect of external disturbance to an H_infinity norm constraint. The results of simulation are given to show effectiveness of the proposed method.

The core of exam management system is how to generate test paper automatically. The existing algorithmic is difficult to simultaneously achieve the requirements with efficient, random, flexible and expansive performance. In this paper, we introduce the maximum flow algorithm of the upper and lower bounds in the graph theory, create a test paper generation model based on constraint conditions, and implement the test paper generation under complex constraints. In addition, to illustrate the success rate and efficiency, the system generated automatically test papers on proposition needs. In turn, it verifies the correctness and rationality of the model. The algorithm proposed in this paper will provide theoretical and technical support for other systems, and it further promotes the development of the exam management system.

Two kinds of redundant constraints in mechanism and the application are discussed in this article.The calculation method of degree of freedom are given about two kinds of redundant constraints. The roles of redundant constraint for mechanism s function is analysed.Some questions is noticed in mechanism design.

The paper presents the determination of the constraint forces acting in the human upper limb joints, using the inverse dynamic analysis procedure based on Lagrange multipliers method. The kinematics parameters time variation laws were established through experiments for the considered driving joints. The constraint forces time variation laws define the database for the dynamic analysis using the finite element method and for dimensioning an exoprosthetic system for later rehabilitation of the human upper limb motion.

Focusing on electric automation with the reactive optimization for power system which is a nonlinear object with multiple variables and constraint conditions, the paper presents an optimal method based on Taboo Search and Genetic Algorithm, which inherits and develops the advantages of multiple search and high robust performance of Genetic Algorithm, and the high climbing ability of Taboo Search to improve the convergence performance and speed. The simulation for IEEE30 node system proves that the method introduced in the paper is appropriate and efficient in the field of electric automation.

In order to study the soil nail optimization of foundation pit and obtain the global optimal solution, this paper establishes the predictive model of response surface by combining uniform test design(UD) and the support vector machine(SVM) technology. In order to avoid the disadvantages of large amount of calculation and low efficiency in heuristic algorithm, and to gain the optimal model of the explicitly analytical function in gradient algorithm, based on the predictive model of response surface under the constraint conditions, the foundation pit soil nailing is optimized through the application of enumerative algorithm. Through an engineering example, it is showed that is a time-saving method and don't need explicitly analytical model. Meanwhile, it can obtain the global optimal solution.