气体分馏过程工艺条件的优化

针对某石化厂气体分馏装置工艺流程进行了模拟计算 ,提出了降低丙烯排放量及各塔热负荷的操作条件调优方案 ,并进行了优化计算和实施。优化前后的结果比较表明 :在确保主产品丙烯的产量和纯度的条件下 ,各塔热负荷的总和降低了 9 2 % ,提高了经济效益     

城市主干路交通流多目标优化控制

提出一种城市主干路交通流多目标优化控制方法 ,分析了多目标优化的性能指标及其约束条件 .用线性预估方法预估单个交叉路口下一周期的车流量 ,模糊推算单个路口周期大小 ,用遗传算法优化平均车辆延误 ,获得每个路口的绿信比 ,在此基础上 ,再用遗传算法优化整条主干路的交通流量 ,获得主干路统一周期 ,最后 ,将周期的值根据绿信比分配到每个路口的各个相位 ,控制信号灯的转换 .仿真结果表明该方法优化性能良好 ,性能稳定     

Optimal design of unit hydrographs using probability distribution and genetic algorithms

A nonlinear optimization model is developed to transmute a unit hydrograph into a probability distribution function (PDF). The objective function is to minimize the sum of the square of the deviation between predicted and actual direct runoff hydrograph of a watershed. The predicted runoff hydrograph is estimated by using a PDF. In a unit hydrograph, the depth of rainfall excess must be unity and the ordinates must be positive. Incorporation of a PDF ensures that the depth of rainfall excess for the unit hydrograph is unity, and the ordinates are also positive. Unit hydrograph ordinates are in terms of intensity of rainfall excess on a discharge per unit catchment area basis, the unit area thus representing the unit rainfall excess. The proposed method does not have any constraint. The nonlinear optimization formulation is solved using binary-coded genetic algorithms. The number of variables to be estimated by optimization is the same as the number of probability distribution parameters; gamma and log-normal probability distributions are used. The existing nonlinear programming model for obtaining optimal unit hydrograph has also been solved using genetic algorithms, where the constrained nonlinear optimization problem is converted to an unconstrained problem using penalty parameter approach. The results obtained are compared with those obtained by the earlier LP model and are fairly similar.     

A combined approach to solve the redundancy optimization problem for multi-state systems under repair policies

This paper combines universal moment generating function technique with stochastic Petri nets to solve the redundancy optimization problem for multi-state systems under repair policies. Redundant elements are included in order to achieve a desirable level of production availability. The elements of the system are characterized by their cost, performance and availability. These elements are chosen from a list of products available on the market. The number of repair teams is less than the number of reparable elements, and a repair policy specifies the maintenance priorities between the system elements. A heuristic is proposed to determine the minimal cost system configuration under availability constraints. This heuristic, first applies universal moment generating function technique to evaluate the system availability, assuming unlimited maintenance resources. Once a preliminary solution is found by the optimization algorithm, stochastic Petri nets are used to model different repair policies, and to find the best system configuration (architecture and number of repairmen) in terms of global performance (availability and cost). This combined procedure is applied to a reference example.     

Reliability Based Design Optimization Using Design Explorer

Experimental design methods can be applied to engineering design activities to understand which variables affect the system under consideration, how these variables affect the system, and how to select variable settings that will give uniformly long life to the system. The objective of this paper is to demonstrate the use of Design and Analysis of Computer Experiment (DACE) methods (Sacks, J. et al., 1989) and design optimization via the Surrogate Management Framework (Booker, A. J. et al., 1999; Audet, C. et al., 2000) on reliability optimization problems. Reliabilities are calculated using the Probabilistic Structural Analysis Method (Palle Thoft–Christensen and Baker, 1982; Achintya Haldar and Sankaran Mahadevan, 2000), a method for estimation of reliabilities and reliability indices for a structural model given probability distributions for design variables and “environmental” variables such as loads. By maximizing reliability, or minimizing the probability of failure, we attempt to achieve a minimum cost design that is affected minimally by the variability in the design variables.     

济钢烧结机技术改造

济钢第一烧结厂2×90m2烧结机为提高烧结矿产量,实施了工艺优化及自动化改造,解决了设备存在的问题,优化了烧结技术指标,取得了良好效果。     

唐钢大盘重碳素焊条钢热轧盘条的研制

介绍唐钢大盘重碳素焊条钢热轧盘条的研制及生产情况。针对该钢种化学成分及力学性能进行了统计、回归分析 ,并对化学成分进行优化     

安钢3#高炉优化操作的生产实践

为稳定高炉炉况，改善高炉操作指标，安钢3^#高炉进行了优化操作实践，取得了较好的效果。     

Decision-making with uncertain data: Bayesian linear programming approach

This paper deals with decision making in a real time optimization context under uncertain data by linking Bayesian networks (BN) techniques (for uncertainties modeling) and linear programming (LP, for optimization scheme) into a single framework. It is supposed that some external events sensed in real time are susceptible to give relevant information about data. BN consists in graphical representation of probabilistic relationship between variables of a knowledge system and so permit to take into account uncertainty in an expert system by bringing together the classical artificial intelligence (AI) approach and statistics approach. They will be used to estimate numerical values of parameters subjected to the influence of random events for a linear programming program that perform optimization process in order to select optimal values of decision variables of a certain real time decision-making system.     

新疆灌溉用水定额分区初步研究

在综合分析新疆各地区地形地貌、气候特征、水资源状况、种植结构、农业灌溉用水现状和经济发展水平等因素基础上,采用共区优选法对新疆灌溉用水定额进行分区,并提出相应的改善措施。该结果可为提高新疆灌溉用水率和用水效率,以及为灌溉管理节水提供决策参考。