基于混合优化算法的关节臂式测量机参数标定

为进一步提高关节臂式坐标测量机等高机动性精密测量设备的测量精度,使用D-H矩阵法建立其关节坐标转换数学模型并据此推导出参数误差模型.针对非线性多参数标定问题,通过变换分析消除了最小二乘法求解时矩阵中的冗余参数,降低了计算的复杂性.设定判定准则并实现最小二乘法和模拟退火算法的混合,提出了一种基于混合优化算法的参数标定方法,解决了LM算法的初值设定和SA算法的搜索效率逐步降低的问题.实验结果表明:关节臂式测量机参数经混合优化算法标定后,参数的误差范围有了显著的缩小,单点重复性误差的平均值减小了1.746 mm,长度误差的平均值减小了0.941 mm,测量误差得到了进一步的抑制.     

Stochastic techniques for global optimization: A survey of recent advances

In this paper stochastic algorithms for global optimization are reviewed. After a brief introduction on random-search techniques, a more detailed analysis is carried out on the application of simulated annealing to continuous global optimization. The aim of such an analysis is mainly that of presenting recent papers on the subject, which have received only scarce attention in the most recent published surveys. Finally a very brief presentation of clustering techniques is given.     

Scale Invariance Properties in the Simulated Annealing Algorithm

The Boltzmann distribution used in the steady-state analysis of the simulated annealing algorithm gives rise to several scale invariant properties. Scale invariance is first presented in the context of parallel independent processors and then extended to an abstract form based on lumping states together to form new aggregate states. These lumped or aggregate states possess all of the mathematical characteristics, forms and relationships of states (solutions) in the original problem in both first and second moments. These scale invariance properties therefore permit new ways of relating objective function values, conditional expectation values, stationary probabilities, rates of change of stationary probabilities and conditional variances. Such properties therefore provide potential applications in analysis, statistical inference and optimization. Directions for future research that take advantage of scale invariance are also discussed.     

Intelligent Control Mechanism of Part Picking Operations of Automated Warehouse

This paper studies the part picking operations of a ut omated warehouse. It assumed the demand of picking orders of automated warehouse are dynamic generated. Once the picking orders of certain period of time are kn own, it is necessary to decide an efficient order picking sequence and routing t o minimize the total travel distance to complete those orders. Assumed there are n i items to be picked in order O i. Each item in the picking ord er is located in different locations in the warehouse. Since i...     

现代优化计算方法在蛋白质结构预测中的应用

现代优化计算方法在蛋白质结构预测中占有重要地位.简要地介绍了模拟退火算法,遗传算法,人工神经网络和图论算法在蛋白质结构预测中的应用.对国内外近年来应用这些算法,特别是在蛋白质构象搜索问题中,解决蛋白质结构预测的研究作了回顾,并分析、比较了这几种算法的效果和特点.     

通过实测室温确定住宅的自然通风状况

住宅自然通风状况的研究有助于住宅设计,使之更加有利于改善空气品质和节能。通过分析比较实测室温和模拟室温,根据状态空间法逐时确定出房间的通风换气频率。并以北京市的3户住宅为研究对象,从以下几个方面讨论计算结果的有效性,模拟室温的计算误差满足精度要求;计算通风换气频率一般小于10h-1,但最高可达50h-1,同时,计算通风换气频率的变化表现出了风压和住户调节行为的影响。故计算通风换气频率大体上符合住宅实际的自然通风状况。     

Parallelization of population-based multi-objective meta-heuristics: An empirical study

In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of problems cannot be solved exactly as they have very large and highly complex search spaces. Recently, meta-heuristic approaches have become important tools for solving multi-objective problems encountered in industry as well as in the theoretical field. Most of these meta-heuristics use a population of solutions, and hence the runtime increases when the population size grows. An interesting way to overcome this problem is to apply parallel processing. This paper analyzes the performance of several parallel paradigms in the context of population-based multi-objective meta-heuristics. In particular, we evaluate four alternative parallelizations of the Pareto simulated annealing algorithm, in terms of quality of the solutions, and speedup.     

模拟退火法在吸收薄膜的椭偏反演算法中的应用

将一种广泛用于求解复杂系统优化问题的技术－－模拟退火法－－用来求解椭偏反演方程。首先假设一个薄膜模型，计算出其相应的椭偏参数（Ψ，Δ）的值，在这个计算值的基础上加入不同标准偏差的高斯噪声；然后将加入噪声后的值（Ψm,Δm)作为模拟的测量数据，采用模拟退火算法进行求解，验证得知这种方法求得的薄膜参数很接近于假设的薄膜模型参数的真值，与其他文献的报道结果一致，而且在扩大搜寻范围时，仍然可以得到准确解，从而证明了该方法的可行性以及有效性。     

Parking Capacity and Pricing in Park'n Ride Trips: A Continuous Equilibrium Network Design Problem

In this paper we consider the problem of designing parking facilities for park'n ride trips. We present a new continuous equilibrium network design problem to decide the capacity and fare of these parking lots at a tactical level. We assume that the parking facilities have already been located and other topological decisions have already been taken.The modeling approach proposed is mathematical programming with equilibrium constraints. In the outer optimization problem, a central Authority evaluates the performance of the transport network for each network design decision. In the inner problem a multimodal traffic assignment with combined modes, formulated as a variational inequality problem, generates the share demand for modes of transportation, and for parking facilities as a function of the design variables of the parking lots. The objective is to make optimal parking investment and pricing decisions in order to minimize the total travel cost in a subnetwork of the multimodal transportation system.We present a new development in model formulation based on the use of generalized parking link cost as a design variable.The bilevel model is solved by a simulated annealing algorithm applied to the continuous and non-negative design decision variables. Numerical tests are reported in order to illustrate the use of the model, and the ability of the approach to solve applications of moderate size.     

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.