A Tentative Research on Complexity of Automatic Programming

In this paper, based on the following theoretical framework: Evolutionary Algorithms + Program Structures = Automatic Programming , some results on complexity of automatic programming for function modeling is given, which show that the complexity of automatic programming is an exponential function of the problem dimension N , the size of operator set ｜F｜ and the height of the program parse tree H . Following this results, the difficulties of automatic programming are discussed. Some function models discovered automatically from database by evolutionary modeling method are given, too.

Static response analysis of structures with interval parameters using the second-order Taylor series expansion and the DCA for QB

In this paper, based on the second-order Taylor series expansion and the difference of convex functions algo- rithm for quadratic problems with box constraints （the DCA for QB）, a new method is proposed to solve the static response problem of structures with fairly large uncertainties in interval parameters. Although current methods are effective for solving the static response problem of structures with interval parameters with small uncertainties, these methods may fail to estimate the region of the static response of uncertain structures if the uncertainties in the parameters are fairly large. To resolve this problem, first, the general expression of the static response of structures in terms of structural parameters is derived based on the second-order Taylor series expansion. Then the problem of determining the bounds of the static response of uncertain structures is transformed into a series of quadratic problems with box constraints. These quadratic problems with box constraints can be solved using the DCA approach effectively. The numerical examples are given to illustrate the accuracy and the efficiency of the proposed method when comparing with other existing methods.

The Study and Development of Plant Management Information System (PMIS) Of NanHua Group Compay

In order to make management scientific, standard and intensive, more and more companies pay attention to plant management. Tlie system presented in this paper aims at helping NanHua Group Co. to improve its plant management level. This paper emphasizes the importance of plant management to NanHua Group Co. and mainly discusses the PMIS and how to implement plant management based on the contents of modern plant management. This part is the core of this paper. The final part sums up the research work and results.

An Improved Graphic Representation for Structured Program Design

In this paper,an improved graphic representation for Structured Program Design——N-S-Z (Nassi-Shneiderman-Zhou Diagram)is proposed.It not only preserves the advantages of the conventional graphic and non-graphic representations,but also adds some new features which will enhance the representa- tive power of the original diagram.

Proximal-Based Pre-correction Decomposition Methods for Structured Convex Minimization Problems

This paper presents two proximal-based pre-correction decomposition methods for convex minimization problems with separable structures.The methods,derived from Chen and Teboulle’s proximal-based decomposition method and He’s parallel splitting augmented Lagrangian method,remain the nice convergence property of the proximal point method and could compute variables in parallel like He’s method under the prediction-correction framework.Convergence results are established without additional assumptions.And the efficiency of the proposed methods is illustrated by some preliminary numerical experiments.

A Methodology for Development of Software Composite-Metrics for Program Control-Flow Structure

This paper reports on a pioneer effort for the establishment of a software composite metric with key capability of distinguishing among different structures. As a part of this effort most of the previously proposed program control-flow complexity metrics are evaluated. It is observed that most of these metrics are inherently limited in distinguishing capability. However, the concept of composite metrics is potentially useful for the development of a practical metrics. This paper presents a methodology for the develop- ment of a practical composite metric using statistical techniques. The proposed metric differs from all previous metrics in 2 ways: (1) It is based on an overall structural analysis of a given program in deeper and broader context. It captures various structural measurements taken from all existing structural levels; (2) It unifies a set of 19 important structural metrics. The compositing model of these metrics is based on statistical techniques rather than on an arbitrary method. Experinces with the pro- posed metric clearly indicate that it distinguishes different structures better than the previous metrics.

Parameter Ecology for Feedback Vertex Set

This paper deals with the FEEDBACK VERTEX SET problem on undirected graphs, which asks for the existence of a vertex set of bounded size that intersects all cycles. Due it is theoretical and practical importance,the problem has been the subject of intensive study. Motivated by the parameter ecology program we attempt to classify the parameterized and kernelization complexity of FEEDBACK VERTEX SET for a wide range of parameters.We survey known results and present several new complexity classifications. For example, we prove that FEEDBACK VERTEX SET is fixed-parameter tractable parameterized by the vertex-deletion distance to a chordal graph. We also prove that the problem admits a polynomial kernel when parameterized by the vertex-deletion distance to a pseudo forest, a graph in which every connected component has at most one cycle. In contrast, we prove that a slightly smaller parameterization does not allow for a polynomial kernel unless NP coNP=poly and the polynomial-time hierarchy collapses.