Analysis of Static Simulated Annealing Algorithms

Generalized hill climbing (GHC) algorithms provide a framework for modeling local search algorithms to address intractable discrete optimization problems. This paper introduces a measure for determining the expected number of iterations to visit a predetermined objective function level, given that an inferior objective function level has been reached in a finite number of iterations. A variation of simulated annealing (SA), termed static simulated annealing (S²A), is analyzed using this measure. S²A uses a fixed cooling schedule during the algorithm execution. Though S²A is probably nonconvergent, its finite-time performance can be assessed using the finite-time performance measure defined in this paper.     

An existence result for a two‐phase Stefan problem arising in metal casting

We present a model arising from the thermal modelling of two metal casting processes. We consider an enthalpy formulation for this two‐phase Stefan problem in a time varying three‐dimensional domain and consider convective heat transfer in the liquid phase. Then, we introduce a weak formulation in a fixed domain, by means of a suitable transformation. Existence of solution is obtained by applying an abstract theorem. The proof of this theorem is done by taking an implicit discretization in time together with a regularization. By passing to the limit in the regularization parameter and in the time step, we obtain the existence of solution of the continuous problem. Copyright © 2005 John Wiley & Sons, Ltd.     

Lagrangean heuristics combined with reoptimization for the 0-1 bidimensional knapsack problem

First, this paper deals with lagrangean heuristics for the 0-1 bidimensional knapsack problem. A projected subgradient algorithm is performed for solving a lagrangean dual of the problem, to improve the convergence of the classical subgradient algorithm. Secondly, a local search is introduced to improve the lower bound on the value of the biknapsack produced by lagrangean heuristics. Thirdly, a variable fixing phase is embedded in the process. Finally, the sequence of 0-1 one-dimensional knapsack instances obtained from the algorithm are solved by using reoptimization techniques in order to reduce the total computational time effort. Computational results are presented.     

Monitoring the Aggregation of Dansyl Chloride in Acetone through Fluorescence Measurements

The aggregation of dansyl chloride (DNS-Cl) in acetone has been studied in detail by steady-state fluorescence techniques.It has been demonstrated that DNS-Cl is stable in acetone during purification and aggregation study processes.The aggregates are not solvolyzed in acetone,and do not take part n any chemical reactions either.It has been found that DNS-Cl tends to aggregate even when its concentration is much lower than its solubility in acetone.The aggregation is reversible,and both the aggregation and the deaggregation are very slow processes.Introduction of SDS has a positive effect upon the formation and stabilization of the aggregates.     

硅一体化薄膜微电极器件及其应用

提出用发展中的硅微机械加工技术设计制作硅一体化薄膜微电极器件．这类微电化学器件具有微电极所特有的全部优点，而且由于结构上的一体化，便于器件整体的微型化和集成化．试用薄膜微电极器件电流法常温直接检测ＣＯ２气体，取得了满意的结果。设想通过器件三维构型设计的改进和完善，器件工作的长期稳定性可望进一步提高．     

Pure adaptive search in global optimization

Pure adaptive seach iteratively constructs a sequence of interior points uniformly distributed within the corresponding sequence of nested improving regions of the feasible space. That is, at any iteration, the next point in the sequence is uniformly distributed over the region of feasible space containing all points that are strictly superior in value to the previous points in the sequence. The complexity of this algorithm is measured by the expected number of iterations required to achieve a given accuracy of solution. We show that for global mathematical programs satisfying the Lipschitz condition, its complexity increases at mostlinearly in the dimension of the problem.This work was supported in part by NATO grant 0119/89.     

搜索三个目标

本文通过建立简洁而有效的搜索方法 ,证明了对于无穷多个n来说 ,三个目标的最优搜索问题的最小试验次数等于信息论下界 .同时也研究了上述问题的修正情形 ,证明了对于所有整数n来说 ,对应的最小试验次数或者等于信息论下界或者超过信息论下界 1次并且对于无穷多个区间 ,信息论下界均是可以达到的 .     

On a new stochastic global optimization algorithm based on censored observations

In this paper a new algorithm is proposed for global optimization problems. The main idea is that of modifying a standard clustering approach by sequentially sampling the objective function while adaptively deciding an appropriate sample size. Theoretical as well as computational results are presented.     

精确搜索下的非线性共轭梯度法

该文提出一种无约束优化非线性共轭梯度法，证明了精确线性 搜索下的全局收敛性。当目标函数为一致凸函数时，证明了算法具有线性收敛速度。数值实验表明算法对于求解实际问题是有效的。