Two-pattern strings II—frequency of occurrence and substring complexity

The previous paper in this series introduced a class of infinite binary strings, called two-pattern strings, that constitute a significant generalization of, and include, the much-studied Sturmian strings. The class of two-pattern strings is a union of a sequence of increasing (with respect to inclusion) subclasses T_λ of two-pattern strings of scope λ, λ=1,2,…. Prefixes of two-pattern strings are interesting from the algorithmic point of view (their recognition, generation, and computation of repetitions and near-repetitions) and since they include prefixes of the Fibonacci and the Sturmian strings, they merit investigation of how many finite two-pattern strings of a given size there are among all binary strings of the same length. In this paper we first consider the frequency f_λ(n) of occurrence of two-pattern strings of length n and scope λ among all strings of length n on {a,b}: we show that lim_n→∞f_λ(n)=0, but that for strings of lengths n2λ, two-pattern strings of scope λ constitute more than one-quarter of all strings. Since the class of Sturmian strings is a subset of two-pattern strings of scope 1, it was natural to focus the study of the substring complexity of two-pattern strings to those of scope 1. Though preserving the aperiodicity of the Sturmian strings, the generalization to two-pattern strings greatly relaxes the constrained substring complexity (the number of distinct substrings of the same length) of the Sturmian strings. We derive upper and lower bounds on C₁(k) (the number of distinct substring of length k) of two-pattern strings of scope 1, and we show that it can be considerably greater than that of a Sturmian string. In fact, we describe circumstances in which lim_k→∞(C₁(k)−k)=∞.     

A unifying look at the Apostolico–Giancarlo string-matching algorithm

String matching is the problem of finding all the occurrences of a pattern in a text. We present a new method to compute the combinatorial shift function (“matching shift”) of the well-known Boyer–Moore string matching algorithm. This method implies the computation of the length of the longest suffixes of the pattern ending at each position in this pattern. These values constituted an extra-preprocessing for a variant of the Boyer–Moore algorithm designed by Apostolico and Giancarlo. We give here a new presentation of this algorithm that avoids extra preprocessing together with a tight bound of 1.5n character comparisons (where n is the length of the text).     

Fast and flexible packed string matching

Searching for all occurrences of a pattern in a text is a fundamental problem in computer science with applications in many other fields, like natural language processing, information retrieval and computational biology. In the last two decades a general trend has appeared trying to exploit the power of the word RAM model to speed-up the performances of classical string matching algorithms. In this model an algorithm operates on words of length w, grouping blocks of characters, and arithmetic and logic operations on the words take one unit of time.In this paper we use specialized word-size packed string matching instructions, based on the Intel streaming SIMD extensions (SSE) technology, to design a very fast string matching algorithm. We evaluate our solution in terms of efficiency, stability and flexibility, where we propose to use the deviation in running time of an algorithm on distinct equal length patterns as a measure of stability.From our experimental results it turns out that, despite their quadratic worst case time complexity, the new presented algorithm becomes the clear winner on the average in many cases, when compared against the most recent and effective algorithms known in literature.     

Extracting approximate patterns

In this paper, we define a family of patterns with don't cares occurring in a text. We call them primitive patterns. The set of primitive patterns forms a basis for all the maximal patterns occurring in the text. The number of primitive patterns is smaller than other known basis.

We present an incremental algorithm that computes the primitive patterns occurring at least q times in a text of length n, given the N primitive patterns occurring at least q−1 times, in time O(|Σ|Nn²logn), where Σ is the alphabet. In the particular case where q=2, the complexity in time is only O(|Σ|n²logn). We also give an algorithm that decides if a given pattern is primitive in a given text. These algorithms are generalized, taking many sequences in input. Finally, we give a solution for reducing the number of patterns of interest by using scoring techniques, as we show that the number of primitive patterns is exponential.     

Pattern Matching with Swaps

Let a text string T of n symbols and a pattern string P of m symbols from alphabet Σ be given. A swapped version T′ of T is a length n string derived from T by a series of local swaps (i.e., t′_ℓ ← t_ℓ + 1 and t′_ℓ + 1 ← t_ℓ), where each element can participate in no more than one swap. The pattern matching with swaps problem is that of finding all locations i for which there exists a swapped version T′ of T with an exact matching of P in location i of T′. It has been an open problem whether swapped matching can be done in less than O(nm) time. In this paper we show the first algorithm that solves the pattern matching with swaps problem in time o(nm). We present an algorithm whose time complexity is O(nm^1/3 log m log σ) for a general alphabet Σ, where σ = min(m,Σ).     

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.     

The analysis of evolutionary algorithms on sorting and shortest paths problems

The analysis of evolutionary algorithms is up to now limited to special classes of functions and fitness landscapes. E.g., it is not possible to characterize the set of TSP instances (or another NP-hard combinatorial optimization problem) which are solved by a generic evolutionary algorithm (EA) in an expected time bounded by some given polynomial. As a first step from artificial functions to typical problems from combinatorial optimization, we analyze simple EAs on well-known problems, namely sorting and shortest paths. Although it cannot be expected that EAs outperform the well-known problem specific algorithms on these simple problems, it is interesting to analyze how EAs work on these problems. The following results are obtained:– Sorting is the maximization of sortedness which is measured by one of several well-known measures of presortedness. The different measures of presortedness lead to fitness functions of quite different difficulty for EAs.– Shortest paths problems are hard for all types of EA, if they are considered as single-objective optimization problems, whereas they are easy as multi-objective optimization problems.     

改进二元分布估计算法求解置换流水车间调度问题

针对置换流水车间调度这类组合最优化问题的求解,提出了一种改进二元分布估计算法(Improved binary estimation distribution algorithm, I-EDA)。算法以二元分布估计算法为架构,使用NEH(Nawaz-Enscore-Ham)启发式算法生成初始解,提高了初始解的质量;通过对优势解的统计采样构建位置矩阵模型和链接矩阵模型,依照两个矩阵模型的合并概率组合链接区块产生子代。提出了NEH插入式重组策略和基于位置概率的交换策略和两种全新局部搜索机制替代原二元分布估计算法的相邻交换法,以进一步筛选优势解。最后通过对Reeves标准测试集的仿真实验和算法比较验证了所提出算法的有效性。     

线性约束优化问题的开关算法模型及其应用

本文利用开关函数．建立了解线性约束优化问题的一个组合型可行方向法─—开关算法模型，并给出了其收敛性质，从而统一、推广了包括起线性收敛的算法在内的常见的可行方向法．依此模型，具体构造了一类起线性收敛的新算法．     

An efficient heuristic algorithm for minimum matching

We give a new heuristic algorithm for minimum matching problems and apply it to the Euclidean problem with random vertices in 2 dimensions. The algorithm is based on simulated annealing and performs in practice faster than previous heuristic algorithms yielding suboptimal solutions of the same good quality. From configurations with up toN=20.000 vertices in the unit square we estimate that the length of a minimum matching scales asymptotically asLN with (=0.3123±0.0016.

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Zusammenfassung Wir stellen einen neuen heuristischen Algorithmus für minimale Matching-Probleme vor und wenden diesen auf das euklidische Problem mit zufÄlliger Punkteverteilung in 2 Dimensionen an. Auf Simulated Annealing basierend lÄuft der Algorithmus schneller als frühere heuristische Algorithmen und erreicht dabei suboptimale Lösungen gleich guter QualitÄt. Aus Konfigurationen mit bis zuN=20.000 Punkten im Einheitsquadrat schÄtzen wir, da\ für die LÄnge des minimalen Matchings asymptotischLN mit=0.3123±0.0016 gilt.

     

三维装箱问题的模型与改进遗传算法

三维装箱问题是一类NP-hard的组合优化问题,构建一个适当的数学模型并设计高效快速的算法具有重要的理论和现实意义.该文将箱子空间划分为立方体单元,依此构建三维装箱问题的混合整数规划模型,并通过改进遗传算法求解,剔除大量不可行解提高了收敛速度.实验结果表明此算法运算过程及结果稳定,具有较强的实际应用价值,能有效解决复杂的三维装箱问题.     

改进的多属性群决策共识方法及其在图书供应商选择中的应用

针对多属性群决策问题,提出了一种改进的加型集结共识方法.在每轮决策中,共识一致性指标较小的决策个体都修改其偏差较大的偏好,能快速使参与决策的个体对各属性形成满意的一致性意见.数值实验也表明该共识方法是合理有效的.     

Squares of characters and finite groups

Let G be a finite group and χ be an irreducible complex character. We study the character χ² in the case that χ(1) is a prime power.     

Shortest paths algorithms: Theory and experimental evaluation

We conduct an extensive computational study of shortest paths algorithms, including some very recent algorithms. We also suggest new algorithms motivated by the experimental results and prove interesting theoretical results suggested by the experimental data. Our computational study is based on several natural problem classes which identify strengths and weaknesses of various algorithms. These problem classes and algorithm implementations form an environment for testing the performance of shortest paths algorithms. The interaction between the experimental evaluation of algorithm behavior and the theoretical analysis of algorithm performance plays an important role in our research. This work was done while Boris V. Cherkassky was visiting Stanford University Computer Science Department and supported by the NSF and Powell Foundation grants mentioned below. Andrew V. Goldberg was supported in part by ONR Young Investigator Award N00014-91-J-1855, NSF Presidential Young Investigator Grant CCR-8858097 with matching funds from AT&T, DEC, and 3M, and a grant from Powell Foundation. Corresponding author. This work was done while Tomasz Radzik was a Postdoctoral Fellow at SORIE, Cornell University, and supported by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550, and by the Packard Fellowship of éva Tardos.     

Conjugacy Classes and Characters for Extensions of Finite Groups

Let H be an extension of a finite group Q by a finite group G. Inspired by the results of duality theorems for tale gerbes on orbifolds, the authors describe the number of conjugacy classes of H that map to the same conjugacy class of Q. Furthermore, a generalization of the orthogonality relation between characters of G is proved.     

Finite convergence of algorithms for nonlinear programs and variational inequalities

Algorithms for nonlinear programming and variational inequality problems are, in general, only guaranteed to converge in the limit to a Karush-Kuhn-Tucker point, in the case of nonlinear programs, or to a solution in the case of variational inequalities. In this paper, we derive sufficient conditions for nonlinear programs with convex feasible sets such that any convergent algorithm can be modified, by adding a convex subproblem with a linear objective function, to guarantee finite convergence in a generalized sense. When the feasible set is polyhedral, the subproblem is a linear program and finite convergence is obtained. Similar results are also developed for variational inequalities.The research of the first author was supported in part by the Office of Naval Research under Contract No. N00014-86-K-0173.The authors are indebted to Professors Olvi Mangasarian, Garth McCormick, Jong-Shi Pang, Hanif Sherali, and Hoang Tuy for helpful comments and suggestions and to two anonymous referees for constructive remarks and for bringing to their attention the results in Refs. 13 and 14.     

BOT项目公司的稳定性及股东行为特征研究

将BOT项目公司的股东简化为建设承包商、设备供应商和主要投资人,然后根据假设条件求出了承包商和供应商作假的最优概率,在此基础上的研究表明项目公司的稳定性与作假被查实的罚金密切相关,且当作假的查处成本降低到一定的水平时,项目公司会具有更好的稳定性.在项目公司有三个股东的情况下,股东在意图作假时不会像只有两个股东那样只权衡自己被查实的概率、惩罚的力度和查处自己的成本,同时还会考虑另一股东作假的概率和项目公司股权的分布并且会比较自己作假和另一股东作假的相对收益.最后为投资人建议了一些应对措施.     

Q-Learning Algorithms with Random Truncation Bounds and Applications to Effective Parallel Computing

Motivated by an important problem of load balancing in parallel computing, this paper examines a modified algorithm to enhance Q-learning methods, especially in asynchronous recursive procedures for self-adaptive load distribution at run-time. Unlike the existing projection method that utilizes a fixed region, our algorithm employs a sequence of growing truncation bounds to ensure the boundedness of the iterates. Convergence and rates of convergence of the proposed algorithm are established. This class of algorithms has broad applications in signal processing, learning, financial engineering, and other related fields. G. Yin’s research was supported in part by the National Science Foundation under Grants DMS-0603287 and DMS-0624849 and in part by the National Security Agency under Grant MSPF-068-029. C.Z. Xu’s research was supported in part by the National Science Foundation under Grants CCF-0611750, DMS-0624849, CNS-0702488, and CRI-0708232. L.Y. Wang’s research was supported in part by the National Science Foundation under Grants ECS-0329597 and DMS-0624849 and by the Michigan Economic Development Council.