Optimization technique based on learning automata

Optimization techniques are finding increasingly numerous applications in process design, in parallel to the increase of computer sophistication. The process synthesis problem can be stated as a largescale constrained optimization problem involving numerous local optima and presenting a nonlinear and nonconvex character. To solve this kind of problem, the classical optimization methods can lead to analytical and numerical difficulties. This paper describes the feasibility of an optimization technique based on learning systems which can take into consideration all the prior information concerning the process to be optimized and improve their behavior with time. This information generally occurs in a very complex analytical, empirical, or know-how form. Computer simulations related to chemical engineering problems (benzene chlorination, distillation sequence) and numerical examples are presented. The results illustrate both the performance and the implementation simplicity of this method.Nomenclature c _i penalty probability - cp precision parameter on constraints - D variation domain of the variablex - f(·) objective function - g(·) constraints - i,j indexes - k iteration number - N number of actions - P probability distribution vector - p _i ith component of the vectorP as iterationk - r number of reactors in the flowsheet - u(k) discrete value or action chosen by the algorithm at iterationk - u _i discrete value of the optimization variable in [u _min,u _max] - u _min lowest value of the optimization variable - u _max largest value of the optimization variable - Z random number - x variable for the criterion function - xp precision parameter on criterion function - W(k) performance index unit output at iterationk - ₀, ₁ reinforcement scheme parameters - _p sum of the probability distribution vector components     

Sur une conjecture de M. Kac

Summary We consider the following heat conduction problem. Let K be a compact set in Euclidean space ³. Suppose that K is held at the temperature 1, while the surrounding medium is at the temperature 0 at time 0. Following Spitzer we investigate the asymptotic behaviour of the integral E _K (t) which represents the total energy flow in time t from the set K to the surrounding medium ³–K. An asymptotic expansion is given for E _K (t) which refines a theorem due to Spitzer. This expansion also verifies and improves a formal calculation of Kac. Similar results are proved in higher dimensions. Up to the constant m(K), the quantity E _K (t) can be interpreted as the expected value of the volume of the Wiener sausage associated with K and a d-dimensional Brownian motion. This point of view both plays a major role in the proofs and leads to a probabilistic interpretation of the different terms of the expansion.     

水溶性席夫碱型锰配合物的合成、表征及其模拟超氧化物歧化酶活性研究

以水杨醛为母体, 与胺类化合物缩合形成席夫碱配体, 用分子自组装法合成了一系列水溶性席夫碱型金属锰单核、双核配合物. 通过元素分析、红外光谱对配合物进行了表征, 采用邻苯三酚自氧化法测定了配合物的超氧化物歧化酶(SOD)活性. 结果表明, 这些水溶性锰配合物具有良好的SOD活性.     

Re_2(edt)_4的电子结构和电子吸收光谱的从头算研究

用密度泛函理论中的B3LYP/CEP-4G方法对Re2（edt）4进行了结构优化和自然键轨道计算,并用单电子激发组态相互作用方法（CIS）计算了Re2（edt）4的分子轨道和激发态。结果表明Re-Re之间不存在明显的三重键,进而很好地解释了Re2（edt）4分子的电子吸收光谱。     

麻黄中伪麻黄碱在小鼠组织中的分布研究

为了解麻黄(Herba ephedrae,简称HE)中伪麻黄碱(Pseudoephedrine,简称PE)在小鼠脑、肺、心、肝、肾的分布变化,探讨HE的归经,用GC-MS/SIM法,分析了用药后30、60、120 min PE在小鼠脏器分布量。结果表明,PE于不同时间点在小鼠脏器的分布由多到少的顺序是:30 min时,肺脏(肾脏、肝脏、脑),心脏;60 min时,肾脏,心脏(肝脏),脑,肺脏;120 min时,脑,肾脏,心脏,肝脏(肺脏)。本试验从PE在小鼠体内脏器的分布量初步反映了HE的归经趋势。     

Y2O2S∶Eu3+,Mg2+,Ti4+长余辉材料制备中烧结条件和助熔剂的影响

Y2O2S∶Eu3+;Mg2+;Ti4+长余辉材料制备中烧结条件和助熔剂的影响;Y2O2S∶Eu3+;Mg2+;Ti4+; 烧结条件; 助熔剂; 发光性质