考虑丝束变形和铺层力学方向的铺放线型规划

为规划不连续预浸丝束在构件曲面上的合理排布形式,分析构件外形、预浸丝束变形和铺层力学方向对构件曲面上铺放路径规划的影响,提出一种工程实用的铺放线型规划方法.分别计算当前路径点的力学方向和材料容许铺放方向相对于测地线方向的偏角,通过偏角比例控制系数来确定多约束条件下的铺放方向,依次求得新的路径点,从而实现构件曲面的铺放路径规划;以曲面均匀铺满为目标,引入重叠系数进行线型的覆盖性分析,计算丝束增减的合理位置,完成构件曲面的铺放线型规划.以某自由曲面铺放线型规划为例,验证了该规划方法的有效性.

禁忌搜索在MPLS离线型规划设计中的应用研究

MPLS离线型规划的主要优点是可以实现全局的优化设计,其主要目标是在满足业务QOS要求的前提下,最小化所需要的跳数,并进行合理流量分配以均衡系统负载。最小路径集和流量分配问题(MPSFAP)是NP完全问题。提出了基于禁忌搜索的启发式算法求解MPSFAP问题,仿真结果表明此近似算法能很好地逼近精确解。

运筹学在物流管理中的应用——第二讲 线型规划及其应用

线型规划问题具有成熟的求银方法,可以借助于计算机进行求解,在物流规划中具有广泛的应用.

建立汽车运材线型规划数学模型之初探

本文提供了一个应用于林区木材运输生产计划管理的线型规划数学模型,以解决如何按照使运材总成本最小的原则来安排运材汽车对次的问题;并且结合一个实例,介绍应用该模型的具体计算过程。

白鹤滩水电站坝址区玄武岩水—岩作用模拟及应用研究

采用水—岩作用线型规划的模拟方法,以白鹤滩水电工程为实例,从水化学方面对坝区复杂水文地质条件作定量分析评价。建立由目标函数和约束条件方程组构成的数学模型,利用Excel规划求解的功能对其进行求解。为评价坝区水文地质条件提供了依据。

白鹤滩水电站坝址区玄武岩水-岩作用模拟及应用研究

采用水-岩作用线型规划的模拟方法,以白鹤滩水电工程为实例,从水化学方面对坝区复杂水文地质条件作定量分析评价。建立由目标函数和约束条件方程组构成的数学模型,利用Excel规划求解的功能对其进行求解,为评价坝区水文地质条件提供了依据。

白鹤滩水电站坝址区玄武岩水-岩作用模拟及应用研究

采用水-岩作用线型规划的模拟方法,以白鹤滩水电工程为实例,从水化学方面对坝区复杂水文地质条件作定量分析评价。建立由目标函数和约束条件方程组构成的数学模型,利用Excel规划求解的功能对其进行求解。为评价坝区水文地质条件提供了依据。

最优化配矿算法实现

矿山在没有配矿场的情况下,主要是通过采取控制各采场出矿量的方法控制矿石入选品位的波动.如何控制采场的出矿量,以使矿山获得最佳效益目标?通过分析南京栖霞山矿井下矿石质量管理过程,建立其数学模型,介绍了计算方法,并应用线型规划理论讨论配矿管理过程中相关算法实现等问题.

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.

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.

Mathematical Model and Simulation of Harmful Invasive Plant Control

Plant invasion refers to the phenomenon that some plants grow too fast due to they are far away from the original living environment or predators, affecting the local environment. With the development of tourism and trade, the harm caused by invasive plants will be more and more serious. Therefore, it is necessary to ex- plore an effective method for controlling plant invasion through qualitative and quan- titative research. In this paper, the models were established for the early and late harmful plant invasion control. The huge computation was completed by the com- puter programming to obtain the optimal solutions of the models. The real meaning of the optimal solution was further discussed. Through numerical simulations and discussion, it could be concluded that the quantitative research on the invasive plant control had a certain application value.

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%.

Land Use Allocation Based on Interval Multi-objective Linear Programming Model: A Case Study of Pi County in Sichuan Province

Adjusting and optimizing land use structure is one of the essential approaches to solve the conflict between land supply and demand. In this study,an uncertain interval multi-objective linear programming model was established and applied to analyzing the suitability of land use structure in Pi County of Sichuan Province. An adjustment scheme for optimizing land use structure was proposed on the basis of development planning drawn up by the local government. The results are summarized as follows: 1) the optimal adjustment scope for cropland area ranges from 27 976.75 ha to 31 029.08 ha,and the current area is less than the lower limit of the scope; 2) the optimal adjustment scope for garden land area ranges from 4 736.49 ha to 12 967.11 ha,and the current area is less than the lower limit; 3) the optimal adjustment scope for construction land ranges from 7 761.95 ha to 10 393.18 ha,and the current area is greater than the upper limit; 4) the optimal adjustment scope for industry and mining land ranges from 557.29 ha to 693.54 ha,and the current area exceeds the upper limit; and 5) the areas of forest land,grassland and other agricultural land are within the optimal adjustment scope. In order to maximize comprehensive benefit with the limited resources and the demand of sustainable development,the areas of cropland and garden land are supposed to be expanded properly,while the construction land should be controlled and reduced gradually,and the forest land and other agricultural land can be maintained at the current level in short period.

Adaptive predictive functional control based on Takagi-Sugeno model and its application to pH process

In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network(RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term schedul-ing of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants.

Infeasibility Diagnosis on the Linear Programming Model of Production Planning in Refinery

In order to effectively diagnose the infeasible linear programming (LP) model of production planning in refinery, the article proposed three stages strategy based on constraints’ classification and infeasibility analysis. Generally, infeasibility sources involve structural inconsistencies and data errors, and the data errors are further classified intoⅠ, Ⅱ and Ⅲ. The three stages strategy are: (1) Check data when they are inputted to detect data error Ⅰ and repair them; (2) Inspect data whether they are accorded with material balance before solving the LP model to identify data error Ⅱ and repair them; (3) Find irreducible inconsistent system of infeasible LP model and give diagnosis information priority-ranked to recognize data error Ⅲ and structural inconsistencies. These stages could be automatically executed by computer, and the approach has been applied to diagnose the infeasible model well in our graphic I/O petro-chemical industry modeling system.

A linear programming model for long-term mine planning in the presence of grade uncertainty and a stockpile

The complexity of an open pit production scheduling problem is increased by grade uncertainty. A method is presented to calculate the cost of uncertainty in a production schedule based on deviations from the target production. A mixed integer linear programming algorithm is formulated to find the min- ing sequence of blocks from a predefined pit shell and their respective destinations, with two objectives： to maximize the net present value of the operation and to minimize the cost of uncertainty. An efficient clustering technique reduces the number of var/ables to make the problem tractable. Also, the parameters that control the importance of uncertainty in the optimization problem are studied. The minimum annual mining capacity in presence of grade uncertainty is assessed. The method is illustrated with an oil sand deposit in northern Alberta.

Modeling and optimization methods of integrated production planning for steel plate mill with flexible customization

With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.

Combined mass and heat exchange network synthesis based on stage-wise superstructure model

Integrating multiple systems into one has become an important trend in Process Systems Engineering research field since there is strong demand from the modern industries. In this study, a stage-wise superstructurebased method is proposed to synthesize a combined mass and heat exchange network(CM&HEN) which has two parts as the mass exchange network(MEN) and heat exchange network(HEN) involved. To express the possible heat exchange requirements resulted from mass exchange operations, a so called "indistinct HEN superstructure(IHS)", which can contain the all potential matches between streams, is constructed at first. Then, a non-linear programming(NLP) mathematical model is established for the simultaneous synthesis and optimization of networks. Therein, the interaction between mass exchange and heat exchange is modeling formulated.The NLP model has later been examined using an example from literature, and the effectiveness of the proposed method has been demonstrated with the results.

Bin-objective shape optimization based on linear programming model of arch dam

Bin-objective shape optimization of arch dam based on linear programming model is discussed to minimize both dam volume and maximal tensile stress.The importance of weight coefficient of the above two objectives is chosen according to the value of importance ratio.The influence of weight coefficient to the optimization result is discussed in detail and the numerical example shows that both the model and method proposed is doable.