SASEGASA: A New Generic Parallel Evolutionary Algorithm for Achieving Highest Quality Results

This paper presents a new generic Evolutionary Algorithm (EA) for retarding the unwanted effects of premature convergence. This is accomplished by a combination of interacting generic methods. These generalizations of a Genetic Algorithm (GA) are inspired by population genetics and take advantage of the interactions between genetic drift and migration. In this regard a new selection scheme is introduced, which is designed to directedly control genetic drift within the population by advantageous self-adaptive selection pressure steering. Additionally this new selection model enables a quite intuitive heuristics to detect premature convergence. Based upon this newly postulated basic principle the new selection mechanism is combined with the already proposed Segregative Genetic Algorithm (SEGA), an advanced Genetic Algorithm (GA) that introduces parallelism mainly to improve global solution quality. As a whole, a new generic evolutionary algorithm (SASEGASA) is introduced. The performance of the algorithm is evaluated on a set of characteristic benchmark problems. Computational results show that the new method is capable of producing highest quality solutions without any problem-specific additions.     

Intercomparison of retrieval codes used for the analysis of high-resolution, ground-based FTIR measurements

A rigorous and systematic intercomparison of codes used for the retrieval of trace gas profiles from high-resolution ground-based solar absorption FTIR measurements is presented for the first time. Spectra were analyzed with the two widely used independent, retrieval codes: SFIT2 and PROFFIT9. Vertical profiles of O₃, HNO₃, HDO, and N₂O were derived from the same set of typical observed spectra. Analysis of O₃ was improved by using updated line parameters. It is shown that profiles and total column amounts are in excellent agreement, when similar constraints are applied, and that the resolution kernel matrices are also consistent. Owing to the limited altitude resolution of ground-based observations, the impact of the constraints on the solution is not negligible. It is shown that the results are also compatible for independently chosen constraints. Perspectives for refined constraints are discussed. It can be concluded that the error budget introduced by the radiative transfer code and the retrieval algorithm on total columns deduced from high-resolution ground-based solar FTIR spectra is below 1%.     

On the advantage over a random assignment

We initiate the study of a new measure of approximation. This measure compares the performance of an approximation algorithm to the random assignment algorithm. This is a useful measure for optimization problems where the random assignment algorithm is known to give essentially the best possible polynomial time approximation. In this paper, we focus on this measure for the optimization problems Max‐Lin‐2 in which we need to maximize the number of satisfied linear equations in a system of linear equations modulo 2, and Max‐k‐Lin‐2, a special case of the above problem in which each equation has at most k variables. The main techniques we use, in our approximation algorithms and inapproximability results for this measure, are from Fourier analysis and derandomization. © 2004 Wiley Periodicals, Inc. Random Struct. Alg., 2004     

Heuristic Rejection in Interval Global Optimization

Based on the investigation carried out in Ref. 1, this paper incorporates new studies about the properties of inclusion functions on subintervals while a branch-and-bound algorithm is solving global optimization problems. It is found that the relative place of the global minimum value within the inclusion function value of the objective function at the current interval indicates mostly whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a considerable amount of computation. Illustrative examples are discussed and an extended numerical study shows the advantages of the new approach.     

一种改进的数字散斑相关方法用于检测人的口型变化

提出了一种基于数字散斑相关测量技术的口型变化检测技术,该技术以白光数字散斑相关测量方法为基础,根据实际应用的需要,引入重心算法并进行了改进,可以实时地检测人说话时的口型变化。通过实验表明,提出的方法是一种实用的、快速、高精度的口型变化测试方法,可为今后的唇语识别技术奠定基础。     

蒙山脆枣与枣及酸枣亲缘关系的研究

以蒙山脆枣及山东省内的9个枣品种和32个酸枣类型(株系)为试材,采用形态学分析和RAPD分析,对蒙山脆枣与枣及酸枣的亲缘关系进行研究,并初步探讨了蒙山脆枣的起源及枣的演化过程。形态学性状数据主成分分析结果表明,蒙山脆枣第1主成分值为5.42,第2主成分值为0.64,介于枣品种和酸枣类型之间,地位较为特殊。对形态学性状数据聚类,结果表明,蒙山脆枣先与酸枣1号在6.40阈值处聚为一类,再与大枣品种的聚类群在11.75阈值处聚为1类之后,才与其它酸枣类型的聚类群聚为一类,显示出蒙山脆枣的分类地位介于枣和酸枣之间。进一步的RAPD分析结果表明,蒙山脆枣与酸枣亲缘关系较近。蒙山脆枣果实长2cm左右,外果皮较薄,中果皮较厚,平均单果重为3.64g,叶片纵横径为6.93cm×3.08cm,形态学性状与枣接近,推测蒙山脆枣可能为供试酸枣类型与枣品种的中间类型。     

New Branch-and-Cut Algorithm for Bilevel Linear Programming

Linear mixed 0–1 integer programming problems may be reformulated as equivalent continuous bilevel linear programming (BLP) problems. We exploit these equivalences to transpose the concept of mixed 0–1 Gomory cuts to BLP. The first phase of our new algorithm generates Gomory-like cuts. The second phase consists of a branch-and-bound procedure to ensure finite termination with a global optimal solution. Different features of the algorithm, in particular, the cut selection and branching criteria are studied in details. We propose also a set of algorithmic tests and procedures to improve the method. Finally, we illustrate the performance through numerical experiments. Our algorithm outperforms pure branch-and-bound when tested on a series of randomly generated problems. Work of the authors was partially supported by FCAR, MITACS and NSERC grants.     

How to assess and report the performance of a stochastic algorithm on a benchmark problem: mean or best result on a number of runs?

Some authors claim that reporting the best result obtained by a stochastic algorithm in a number of runs is more meaningful than reporting some central statistic. In this short note, we analyze and refute the main argument brought in favor of this statement.     

Probabilistic Analysis of Condition Numbers for Linear Programming

In this paper, we provide bounds for the expected value of the log of the condition number C(A) of a linear feasibility problem given by a n × m matrix A (Ref. 1). We show that this expected value is O(min{n, m log n}) if n > m and is O(log n) otherwise. A similar bound applies for the log of the condition number C _R(A) introduced by Renegar (Ref. 2).