新型多功能圆管三通过渡线划线规

介绍一种新型圆管三通过渡线划线工具的结构原理和使用方法。

圆管异径三通多功能过渡线划线规

介绍一种新型的划圆管三通过渡线的划线工具的结构原理和使用方法。

会计结帐划线规范小议

划线，在会计业务工作中是一项经常会碰到的工作。填制记帐凭证完成经济业务事项后，如有空行，应自金额栏最后一笔金额数字下的空行处至合计数上的空行处划线注销；在登记帐簿时发生错误，应当将错误的文字或数字划红线注销；结帐时，应当在“本月合计”下面通栏划单红线...

圆管异径三通多功能过渡线划线规设计

介绍一种新型的划圆管三通过渡线的划线工具的结构原理和使用方法

LOCALIZATION ALGORITHM USING DISTANCE AND ANGLE INFORMATION IN WIRELESS SENSOR NETWORKS

A localization algorithm using distance and angle information is proposed in wireless sensor networks. Assuming that node axial orientations are unknown, all angles are measured to calculate the angle differences between two nodes viewed by the third one. Then, localization problems are formulated as convex optimization ones and all geometric relationships among different nodes in the communication range are transformed into linear or quadratic constraints. If all measurements are accurate, the localization problem can be formulated as linear programming （LP）. Otherwise, by incorporating auxiliary variables, it can be regarded as quadratic programming （QP）. Simulations show the effectiveness of the proposed algorithm.

Application of the Sediment Mathematical Modelling on Planned Project of Lingdingyang Bay

Based on the combined hydraulic calculation for the eastern network region at the Pearl River estuary and several outlets to the Lingdingyang Bay, the sediment calculation modelling was introduced in the establishment of the sediment mathematical model for Lingdingyang Bay and the eastern region with one and two dimensional flow calculation. Model adjustment and verification were performed in conjunction with field data. The simulated results coincide well with measured data.In addition the model is applied to predict the shore-line planning scheme of Lingdingyang Bay.The theoretical criterion is provided for the shore line plan in the model.And a new mathematical simulated method is put out to research the planning engineering concerned with one-dimensional net rivers and two-dimensional estuary.

A NEW MODEL AND SOLUTION FOR TRANSPORTATION PROBLEM

Transportation problem has many real world applications, it can be solved by linear programming model, but in most time the model exists more for less paradox, this paper considers the reasons for the paradox and search the way to eliminate the phenomenon. First this paper formulates a loose constrained linear programming model for the transportation problem, and gives the definition of the paradox which exists in it, some preliminary notions and one example is also given. Then it gives a table based algorithm for the loose constrained model, the steps of the algorithm and example will follow. The examples show that: (1) It is not a contradictory that transportation problem exists more for less paradox. (2) The loose constrained model is better used in practice for its less total cost. (3) The algorithm is easy to calculate, to study and highly speed to convergence. Finally, comparied with other ways it shows that the loose constrained model can thoroughly eliminate the paradox.

An Optimal Model for Carbon Sinks of CDM Project to Build a New Countryside Based on Cyclic Economy under Uncertainty

Based on the status and characteristics of Clean Development Mechanism （CDM） renewable energy project and the mode of cyclic economy, aimed at achieving the maximum capacity of carbon sinks in the system, Lvjin Jiayuan—New Countryside Distripark CDM project in Wuchuan County was taken as an example for developing an interval linear programming （ILP） model to optimize the crops planting scheme and cows breeding scheme by using interval optimal method. The case showed that the optimized crops planting scheme and cows breeding scheme obtained from the optimal model was reasonable with relatively preferable overall performance. In the context of meeting economic benefits and fertilizer, electricity demand, [231 287.8, 273 312.7] t of CO2 could be absorbed and fixed, which had increased by [12.94, 33.46]% compared with the feasibility scheme of case project and provided technical support for making the decision in CDM project.

Precise Calculation System of Total Mix Ration for Lactating Cow

[Objective] The paper was to precisely predict nutrient requirements and optimize ration formula, and explore the inherent feature of ration optimization of dairy cow. [Method] Based on cornell net carbohydrate and protein system （CNCPS） with integrating dynamic prediction models on main nutrient requirements of dairy cattle recommended by NRC （2001） and the CNCPS parameter database accumu- lated by Chinese feed database, the ration nutrient requirement dynamic calculation and total mixed ration （TMR） formula optimizing system for Holstein dairy cow was developed using FOXPRO database system and parametric linear programming algo- rithm. [Result] By optimizing a specific cow ration and analyzing its completed nutri- ents, the results showed that this system could entirely consider a lots of nutrient balances, such as concentrate fraction and forage fraction balance, rumen degrad- able protein and rumen undergradable protein balance, crude protein and lactation net energy balance, fibrous substances （ADF, NDF） and non-fiber carbohydrates （NFC） balance, calcium and phosphate balance, electrolytes balance and trace ele- ment balance etc., and could also calculate intestinal amino acid flow in terms of different models. [Conclusion] By using dynamic mathematical equations and comput- erized program, it can be realized for the ration formula design of lactating cow with all-round interoperable but mutual-constraining each other among ration nutrients.

Necessary and Sufficient Conditions in Smooth Programming with Generalized Convexity

Hanson and Mond have grven sets of necessary and sufficient conditions for optimality in constrained optimization by introducing classes of generalized functions, called type Ⅰ functions. Recently, Bector definded univex functions, a new class of functions that unifies several concepts of generalized convexity. In this paper, additional conditions are attached to the Kuhn Tucker conditions giving a set of conditions which are both necessary and sufficient for optimality in constrained optimization, under appropriate constraint qualifications.

A non-monotone Phase-1 method in linear programming

To gain superior computational efficiency, it might be necessary to change the underlying philosophy of the simplex method. In this paper, we propose a Phase-1 method along this line. We relax not only the conventional condition that some function value increases monotonically, but also the condition that all feasible variables remain feasible after basis change in Phase-1. That is, taking a purely combinatorial approach to achieving feasibility. This enables us to get rid of ratio test in pivoting, reducing computational cost per iteration to a large extent. Numerical results on a group of problems are encouraging.

FLIGHT CONFLICT DETECTION AND RESOLUTION

The air traffic control (ATC) systems are facing more and more serious congestive because of the increasing of air traffic flow in China. One of the most available ways to solve the problem is 'free flight' that the pilots may choose the air route and flight speed suitable for them. But this will lead to the difficulties for the controllers. This paper presents how ATC genetic algorithms can be used to detect and to solve air traffic control conflicts in free flight. And it also shows that this algorithm perfectly suits for solving flight conflicts resolution because of its short computing time.

A Modified Algorithm for Nonliear Integer Programming

Based on the analysis to the random sear ch algorithm of LUUS, a modified random directed integer search algorithm (MRDI SA) is given for first time. And a practical example is given to show that the adva ntage of this kind of algorithm is the reliability can’t be infuenced by the ini tial value X (0) and the start search domain R (0) . Besides, i t can be applied to solve the higher dimensional constrained nonlinear integer p rogramming problem.

HIERARCHICAL ITERATIVE GA FOR OPTIMIZATION OF THE PLAN IN COAL MINE CONSTRUCTION

In coal mine construction,to make the optimal plan of complete sets of equipment needs to set up a mixed integer nonlinear programming model,which has many variables and more complicated parameters to set.The problem could hardly be solved using general methods.In this paper a new genetic approach—the hierarchical iterative genetic algorithm (HIGA) was designed to solve it and a satisfactory solution was obtained.

Path-Based Timing Optimization by Buffer Insertion with Accurate Delay Model

An algorithm of path based timing optimization by buffer insertion is presented.The algorithm adopts a high order model to estimate interconnect delay and a nonlinear delay model based on look up table for gate delay estimation.And heuristic method of buffer insertion is presented to reduce delay.The algorithm is tested by industral circuit case.Experimental results show that the algorithm can optimize the timing of circuit efficiently and the timing constraint is satisfied.

Comprehensive decision-making method for optimal location of logistics hubs

A mathematical optimal model is developed to address the problem of logistics hubs location.The method integrates nonlinear programming models and fuzzy comprehensive evaluation,and handles both quantitative and qualitative factors that influence the location of logistics hubs.A mathematical programming model is used to find the optimal candidate sites of the logistics hub based on profit-maximizing criteria.Then a fuzzy comprehensive evaluation method is adopted to determine the final optimal location of those candidate sites by taking account of criteria including stability of policy environment,convenience of transportation(e.g.,easy access to highways/expressways,etc.),rationality of economy,competition and sustainability.Finally,the methodology is demonstrated by a case study of the Transfar Logistics Base in Zhejiang Province.The results verify the method application for logistics hub locations and show how to locate a logistics hub in practice from the case of Transfar Logistics Base.

Analysis of Mine Ventilation Network Using Genetic Algorithm

Aim To determine the global optimal solution for a mine ventilation network under given network topology and airway characteristics. Methods\ The genetic algorithm was used to find the global optimal solution of the network. Results\ A modified genetic algorithm is presented with its characteristics and principle. Instead of working on the conventional bit by bit operation, both the crossover and mutation operators are handled in real values by the proposed algorithms. To prevent the system from turning into a premature problem, the elitists from two groups of possible solutions are selected to reproduce the new populations. Conclusion\ The simulation results show that the method outperforms the conventional nonlinear programming approach whether from the viewpoint of the number of iterations required to find the optimum solutions or from the final solutions obtained.

Fine-Grain Sleep Transistor Insertion for Leakage Reduction

A fine-grain sleep transistor insertion technique based on our simplified leakage current and delay models is proposed to reduce leakage current. The key idea is to model the leakage current reduction problem as a mixed-integer linear programming （MLP） problem in order to simultaneously place and size the sleep transistors optimally. Because of better circuit slack utilization, our experimental results show that the MLP model can save leakage by 79.75%, 93.56%, and 94.99% when the circuit slowdown is 0%, 3%, and 5%, respectively. The MLP model also achieves on average 74.79% less area penalty compared to the conventional fixed slowdown method when the circuit slowdown is 7%.

CONSTRAINT QUALIFICATIONS AND DUAL PROBLEMS FOR QUASI-DIFFERENTIABLE PROGRAMMING

In classical nonlinear programming, it is a general method of developing optimality conditions that a nonlinear programming problem is linearized as a linear programming problem by using first order approximations of the functions at a given feasible point. The linearized procedure for differentiable nonlinear programming problems can be naturally generalized to the quasi differential case. As in classical case so called constraint qualifications have to be imposed on the constraint functions to guarantee that for a given local minimizer of the original problem the nullvector is an optimal solution of the corresponding 'quasilinearized' problem. In this paper, constraint qualifications for inequality constrained quasi differentiable programming problems of type min {f(x)|g(x)≤0} are considered, where f and g are qusidifferentiable functions in the sense of Demyanov. Various constraint qualifications for this problem are presented and a new one is proposed. The relations among these conditions are investigated. Moreover, a Wolf dual problem for this problem is introduced, and the corresponding dual theorems are given.