混合整参数贝塔分布及其应用

本文给出了一个新的指数型分布,它是整参数贝塔分布Be(k+1,n-k)对于整数n的截0至k的截尾泊松分布的混合分布.论文给出了这一分布的统计意义和数字特征,并通过一个例子说明了它的一个应用.

一类可分离非线性混合整规划的填充函数解法

讨论了把一类可分离非线性混合整规划问题转化为解一系列非线性规划 ,整数规划 ,再构造填充函数求解的方法 。

非线性混合整数规划的罚函数解法

主要对非线性混合整规划问题的求解进行探讨。利用罚函数把非线性混合整规划问题转化为等价的非线性规划问题,从而可通过求解一个无约束线性规划问题而得到原问题的最优解。

一类非线性混合整规划的无约束连续化解法

将整系数多项式 0 - 1混合整规划问题化成无约束多项式规划问题。通过解该问题 ,能得到原问题的近似解。处理方法的特点是能够直接处理不等式约束情形 。

非线性混合整数规划的罚函数解法

文[6]中,我们对非线性混合整数规划的解法进行了探讨,利用罚函数把有约束非线性混合整数规划问题化为等价的无约束非线性混合整数规划问题,然后把离散整变量连续化,从而非线性混合整数规划化为与之等价的无约束非线性规划。本文弱化了文[6]中定理1的条件,并得到了相应的结论。

基于压电堆和粘弹性材料的新型整星混合隔振系统

为了降低振动载荷对卫星的影响,采用压电堆和粘弹性材料作为主被动隔振元件,设计一种新型的整星混合隔振系统,并对其隔振原理进行理论分析。通过有限元方法建立该隔振系统的有限元模型并分析其频率响应特性,根据分析结果,运用特征系统实现算法获取系统的最小阶状态空间模型来设计控制器,完成离线仿真。在此基础上,对低柔性模拟卫星进行整星混合隔振试验。仿真和试验结果表明,整星混合隔振系统能够有效地降低运载火箭传递到卫星的振动载荷。与整星被动隔振系统相比,整星混合隔振系统对低频振动分量具有显著的抑制作用,证明了该隔振系统的可行性和有效性,大大提高了卫星的安全性和可靠性。

多元时序和滞后协整混合模型

文章将滞后分析、时序分析、滞后协整分析进行有机整合,建立了多元时序和滞后协整混合预测模型;此外,还提出了反映不同时期向量序列之间协整关系的滞后协整的概念,滞后协整概念的提出能为预测和决策提供更为广阔的思考空间。

多组分同位素分离级联的数值优化方法研究

针对多组分同位素分离级联进行数值优化过程中,存在整型变量与实型变量混合、局部最优解等问题,导致级联的优化难度加大。以连续级联Q级联为参考级联,提出一种改进后的级联数值优化方法,同时对优化变量中的整型与实型进行优化,并引入级联流量自动调整策略,以及含约束条件的单目标罚函数,可以有效避免级联数值优化过程中局部最优解的问题。结果表明,该方法能够有效地进行级联优化,得到接近Q级联的离散级联优化结果,优化后的离散级联总流量接近Q级联总流量,流量分布接近Q级联流量分布。针对同位素级联生产建设实际情况,基于优化后的Q级联构造不同形状的阶梯级联并对其进行优化,使之接近Q级联,可有效实现阶梯级联的优化,降低级联建设成本。

基于网损因子迭代的安全约束机组组合算法

针对考虑安全约束的机组组合(security constrained unit commitment,SCUC)问题,在传统SCUC模型的基础上,建立考虑有功网损及其在电网中分布的SCUC模型,提出一种基于网损因子迭代的SCUC算法。此算法每次迭代先解固定网损因子的SCUC问题,求得机组的运行状态,然后进行交流潮流计算,更新网损因子,进入下一次迭代。针对可能出现的网损因子振荡问题,提出SCUC和经济调度相结合的方法,选择对应发电成本较小的机组启停状态,进行经济调度优化和网损因子迭代计算,直至算法收敛。对IEEE 30和IEEE 118节点系统进行的仿真计算验证了所提算法的正确性和有效性。

复杂工业过程新型控制方法——混杂系统控制理论的研究

系统地评析了基于不同框架的混杂系统的建模、控制、优化、分析与设计问题 ,着重分析了基于混合逻辑动态系统的研究方法 ;指出了研究混杂系统需解决的关键技术问题 。

基于改进算子的免疫遗传算法的电压无功优化

针对电压无功优化问题的特点和免疫遗传算法在求解全局性优化问题中的适用性,应用免疫遗传算法对系统进行电压无功优化。在编码时采用了实整混合编码形式,求抗体相似度时进行了归一化处理,在选择操作时对适应度函数进行了变换,合理的选择变换系数的值,可以保证算法在进化前期保持种群多样性,在进化后期仍能有较快收敛速度,并在交叉变异时实数段和整数段基因采取不同的措施。取IEEE-30节点标准系统为例,利用开发的优化计算程序进行电压无功优化计算,验证了所提出的算法较其他算法在计算和收敛能力上具有优势。

基于模糊PID控制的BTT导弹自动驾驶仪设计

倾斜转弯（bank—to—turn，BTT）BTT导弹在飞行过程中，它的参数是时变且大范围不确定的，因此其数学模型具有一定的不确定性。引入对被控对象模型精确度要求较低的模糊控制法．结合经典PID控制法，设计了三种BTT导弹自动驾驶仪，并对其进行了仿真比较。

Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis

Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

A risk-based methodology for the optimal placement of hazardous gas detectors

Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.

Arterial traffic signal coordination model considering buses and social vehicles

Considering the difference in driving parameters of buses and social vehicles on the arterial,an arterial traffic signal coordination model that takes into account social vehicles and buses on the basis of the maximum bandwidth is proposed.By using the pre-set parameters of a common cycle,green/red duration and known parameters of bus dwell time distribution,link length and vehicle speed and solving the mixed-integer-linear programming and optimizing the signal offsets,the model obtains the signal control parameters of the green bands both of social vehicles and buses.Finally,taking Wangjiang Road in Hefei as an example,simulation and evaluation are carried out by VISSIM.The results show that the new model has 15.2%and 13.2%reduction in average person delay and number of stops,respectively,compared with the traditional coordinated control method.

Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

In this paper, an improved hybrid differential evolution-estimation of distribution algorithm (IHDE-EDA) is proposed for nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) models in engineering optimization fields. In order to improve the global searching ability and convergence speed, IHDE-EDA takes full advantage of differential information and global statistical information extracted respectively from differential evolution algorithm and annealing mechanism-embedded estimation of distribution algorithm. Moreover, the feasibility rules are used to handle constraints, which do not require additional parameters and can guide the population to the feasible region quickly. The effectiveness of hybridization mechanism of IHDE-EDA is first discussed, and then simulation and comparison based on three benchmark problems demonstrate the efficiency, accuracy and robustness of IHDE-EDA. Finally, optimization on an industrial-size scheduling of two-pipeline crude oil blending problem shows the practical applicability of IHDE-EDA.

Strategic mining options optimization:Open pit mining, underground mining or both

Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining. This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP) optimization framework. The MILP formulation maximizes the Net Present Value(NPV) of the reserve when extracted with(i) open pit mining,(ii) underground mining, and(iii) concurrent open pit and underground mining. Comparatively, implementing open pit mining generates a higher NPV than underground mining. However considering the investment required for these mining options, underground mining generates a better return on investment than open pit mining. Also, in the concurrent open pit and underground mining scenario, the optimizer prefers extracting blocks using open pit mining. Although the underground mine could access ore sooner, the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.

Improved Mixed Integer Optimization Approach for Data Rectification with Gross Error Candidates

Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance constrains. But the efficiency will decrease significantly when this method is applled in a large-scale problem because there are too many binary variables involved. In this article, an improved method is proposed in order to gen- erate gross error candidates with reliability factors before data rectification. Candidates are used in the MILP objec- tive function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates. Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.