Robust design in multivariate systems using genetic algorithms

This paper presents a methodology based on genetic algorithms, which finds feasible and reasonably adequate solutions to problems of robust design in multivariate systems. We use a genetic algorithm to determine the appropriate control factor levels for simultaneously optimizing all of the responses of the system, considering the noise factors which affect it. The algorithm is guided by a desirability function which works with only one fitness function although the system may have many responses. We validated the methodology using data obtained from a real system and also from a process simulator, considering univariate and multivariate systems. In all cases, the methodology delivered feasible solutions, which accomplished the goals of robust design: obtain responses very close to the target values of each of them, and with minimum variability. Regarding the adjustment of the mean of each response to the target value, the algorithm performed very well. However, only in some of the multivariate cases, the algorithm was able to significantly reduce the variability of the responses.     

采用改进遗传算法的变压器优化设计

电力机车变压器的优化设计,采用遗传算法是比较好的选择,但传统遗传算法存在一些弊端,文章从编码方式、遗传操作等几个方面探讨了如何对其进行改进,并使用Visual C++编写了一套设计软件,实践证明这种改进是有效的。     

一种改善数据流间带宽公平性的算法研究

公平性问题是衡量网络性能的重要参数。文章提出了一种新的算法,一方面针对非TCP友好流,利用TCP行为估算每个流的丢包可能性,减少具有不同tRTT(回路响应时间)TCP流之间网络带宽的不公平性问题;另一方面,针对非响应流(如UDP流),该算法将使它在进入路由器之前就丢包。实验结果表明新算法可以降低在网络中的丢包率,同时较好地实现流间带宽的公平分配,从而提高了链路的利用率。     

污水管网设计中存在的问题及对策

室外污水管道工程设计是-个实践经验与能动性相结合的过程。在满足规范要求的同时,要根据实际隋况,因地制宜,尽量做到经济合理。分析了当前污水管网系统存在的问题,重点分析了管网设计中存在的问题,并从加强规划管理、改进设计等方面提出了相应对策。     

An improved combinatorial approach for pricing Parisian options

Parisian options are path-dependent options whose payoff depends on whether the underlying asset’s price remains continuously at or above a given barrier over a given time interval. Costabile’s (Decis Econ Finance 25(2):111–125, 2002b) algorithm for pricing Parisian options based on a combinatorial approach in binomial tree has a time complexity of O( n³){O\left( {n^{3}}\right)}. We improve that algorithm to yield one with a time complexity of only O(n²){O\left({n^{2}}\right)}.     

改进菱形运动估计算法研究与实现

针对目前菱形运动估计搜索算法存在的问题,对不同宏块采用相同的搜索策略,而不能根据视频序列的特性,迅速缩小搜索的范围,造成搜索冗余。文章分析了运动矢量的分布相关性,提出了基于起点预测的改进菱形运动估计算法。该算法结合提前中止准则,能改进菱形算法的搜索流程。仿真结果表明,该算法在降低计算复杂度的同时,还可有效地保证搜索精度。     

An integrated algorithm for three-way compositional data

Quality & Quantity - Compositional data with a tridimensional structure are not uncommon in social sciences. The CANDECOMP/PARAFAC model is one of the most adequate techniques for modeling...     

An algorithm for the generalized transportation problem

This paper describes a new computational technique for solving spatial economic equilibrium problems which are generalizations of the classic transportation problem. This technique makes use of a type of algorithm which has been developed in recent years to compute Kakutani fixed points and solve related problems. Existing algorithms for the generalized transportation problem employ quadratic programming, and therefore require that demand and supply functions be linear. By contrast, the algorithm of this paper can handle demand and supply relationships which are nonlinear or even semi-continuous. It can also handle non-constant transport costs and various other complications. The technique is capable of yielding highly accurate solutions, and appears to be computationally efficient on problems of reasonable size.     

An improved empirical Bayes test for positive exponential families

We exhibit an empirical Bayes test δ^* _n for a decision problem using a linear error loss in a class of positive exponential families. This empirical Bayes test δ^* _n possesses the asymptotic optimality, and its associated regret converges to zero with rate n ⁻¹(ln n )⁶ This rate of convergence improves the previous results in the literature in the sense that a faster rate of convergence is achieved under much weaker conditions. Examples are presented to illustrate the performance of the empirical Bayes test δ^* _n     

A process model for concurrent design in manufacturing enterprise information systems

In manufacturing enterprise information systems, concurrent design process is one of the focuses of research on design process management. This study proposes a novel process model for concurrent design based on unified modelling language (UML) and polychromatic sets theory. Model primitives and constructs of UML activity diagram, concurrent design activities, and dynamic changes of concurrent design process are described in the polychromatic sets contour matrix. Based on polychromatic sets theory, the model reduction rules and algorithm are proposed. With the feature-based part design and process planning, a UML model of concurrent design process is developed and mapped into polychromatic sets contour matrix model. The dynamic change, model reduction, path search and time consumption of concurrent design process are analysed, and the direction for improving concurrent design process and shortening product development cycle is suggested.     

An algorithm for panel ANOVA with grouped data

In this paper, we present an algorithm suitable for analysing the variance of panel data when some observations are either given in grouped form or are missed. The analysis is carried out from the perspective of ANOVA panel data models with general errors. The classification intervals of the grouped observations may vary from one to another, thus the missing observations are in fact a particular case of grouping. The proposed Algorithm (1) estimates the parameters of the panel data models; (2) evaluates the covariance matrices of the asymptotic distribution of the time-dependent parameters assuming that the number of time periods, T, is fixed and the number of individuals, N, tends to infinity and similarly, of the individual parameters when T → ∞ and N is fixed; and, finally, (3) uses these asymptotic covariance matrix estimations to analyse the variance of the panel data.     

An optimisation method for complex product design

Designing a complex product such as an aircraft usually requires both qualitative and quantitative data and reasoning. To assist the design process, a critical issue is how to represent qualitative data and utilise it in the optimisation. In this study, a new method is proposed for the optimal design of complex products: to make the full use of available data, information and knowledge, qualitative reasoning is integrated into the optimisation process. The transformation and fusion of qualitative and qualitative data are achieved via the fuzzy sets theory and a cloud model. To shorten the design process, parallel computing is implemented to solve the formulated optimisation problems. A parallel adaptive hybrid algorithm (PAHA) has been proposed. The performance of the new algorithm has been verified by a comparison with the results from PAHA and two other existing algorithms. Further, PAHA has been applied to determine the shape parameters of an aircraft model for aerodynamic optimisation purpose.     

Adaptive learning in an asymmetric auction: genetic algorithm approach

Agent-based simulations are performed to study adaptive learning in the context of asymmetric first-price auctions. Non-linearity of the Nash equilibrium strategies is used to investigate the effect of task complexity on adaptive learning by varying the degree of approximation the agents can handle. In addition, learning in different information environments is explored. Social learning allows agents to imitate each other’s bidding strategies based on their relative success. Under individual learning agents are limited to their own experience. We observe convergence to steady states near the predicted equilibrium in all cases. The ability to learn non-linear functions helps the agents with a non-linear equilibrium strategy but hurts the agents with an almost linear one. Better information about the opponent population has a relatively modest impact. A larger number of strategies to experiment with and an ability to systematically compare strategies by holding a number of factors constant have a comparatively stronger beneficial effect.     

An algorithm for resource allocation with constraints in an input-output framework

In a large corporation or at the national level, planning involves a large number of inter-related activities competing for the same resources. In spite of its rather restrictive assumptions, Leontief's Input-Output model is still one of the best tool for the study of physical and financial flows between activities or economic sectors. A simple algorithm to find its solution when the available resources are limited is presented in this paper. The properties of that algorithm that was incorporated in an inter-industrial model built in Venezuela are proven and are followed by examples of application.

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Riassunto In grandi imprese o in sistemi economici nazionali la pianificazione riguarda un numero elevato di attività interrelate che fanno uso delle stesse risorse. Nonostante le ipotesi di base piuttosto restrittive, il modelloinput-output di Leontief è ancora uno degli strumenti più efficaci per lo studio dei flussi fisici e finanziari tra attività o settori economici.In questo lavoro viene presentato un semplice algoritmo per individuare la soluzione d'un problema di pianificazione quando sono limitati gli ammontari delle risorse. Sono dimonstrate alcune proprietà di questo algoritmo, che fu impiegato su un modello di relazioni interindustriali costruito in Venezuela e sono fornite alcune applicazioni esemplificatrici.

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Versione definitiva pervenuta il 14-2-1983     

An enhanced dynamic hash TRIE algorithm for lexicon search

Information retrieval (IR) is essential to enterprise systems along with growing orders, customers and materials. In this article, an enhanced dynamic hash TRIE (eDH-TRIE) algorithm is proposed that can be used in a lexicon search in Chinese, Japanese and Korean (CJK) segmentation and in URL identification. In particular, the eDH-TRIE algorithm is suitable for Unicode retrieval. The Auto-Array algorithm and Hash-Array algorithm are proposed to handle the auxiliary memory allocation; the former changes its size on demand without redundant restructuring, and the latter replaces linked lists with arrays, saving the overhead of memory. Comparative experiments show that the Auto-Array algorithm and Hash-Array algorithm have better spatial performance; they can be used in a multitude of situations. The eDH-TRIE is evaluated for both speed and storage and compared with the naïve DH-TRIE algorithms. The experiments show that the eDH-TRIE algorithm performs better. These algorithms reduce memory overheads and speed up IR.     

Using forecasted net benefits in designing improved recruitment and selection systems

This paper extends the post hoc application of utility formulae to designing improved recruitment and selection systems. It emphasizes interactive tradeoffs from spending to (I) increase the size of the applicant pool, and (2) increase the accuracy of applicant selection.First, the paper reviews the utility formula. Then it applies the formula towards improving the design of recruitment strategies. Next, the paper examines the dollar costs and benefits of different selection strategies. Finally, it examines the dual impact of recruitment and selection taken together. In short, while recruitment has been both under and overfunded in specific environments, selection has been uniformly underfunded, resulting in substantial opportunity costs to organizations.     

An exchange algorithm for computing the least quartile difference estimator

We propose an exchange algorithm (EA) for computing the least quartile difference estimate in a multiple linear regression model. Empirical results suggest that the EA is faster and more accurate than the usual p-subset algorithm.     

An information theoretical algorithm for analyzing supersaturated designs for a binary response

A supersaturated design is a factorial design in which the number of effects to be estimated is greater than the number of runs. It is used in many experiments, for screening purpose, i.e., for studying a large number of factors and identifying the active ones. In this paper, we propose a method for screening out the important factors from a large set of potentially active variables through the symmetrical uncertainty measure combined with the information gain measure. We develop an information theoretical analysis method by using Shannon and some other entropy measures such as Rényi entropy, Havrda–Charvát entropy, and Tsallis entropy, on data and assuming generalized linear models for a Bernoulli response. This method is quite advantageous as it enables us to use supersaturated designs for analyzing data on generalized linear models. Empirical study demonstrates that this method performs well giving low Type I and Type II error rates for any entropy measure we use. Moreover, the proposed method is more efficient when compared to the existing ROC methodology of identifying the significant factors for a dichotomous response in terms of error rates.     

An approach to define semantics for BPM systems interoperability

This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise’s business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology.

For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.