Ordering is used to reduce the amount of fill-ins in the Cholesky factor of a symmetric positive definite matrix. One of the most efficient ordering methods is the minimum degree ordering algorithm(MDO). In this paper, we provide a few techniques that improve the performance of MDO implemented with the clique storage scheme. First, the absorption of nodes in the cliques is developed which reduces the number of cliques and the amount of storage space required for MDO. Second, we present a modified minimum degree ordering algorithm of which the number of degree updates can be reduced by introducing the lower bounds of degrees. Third, using both the lower and upper bounds of degrees, we develop an approximate minimum degree ordering algorithm. Experimental results show that the proposed algorithm is competitive with the minimum degree ordering algorithm that uses quotient graphs from the points of the ordering time and the nonzeros in the Cholesky factor.

Rapid advances in information technology(IT) and telecommunication systems impact the number and quality of decision-making in organizations. Specifically, middle mangers must posses or develop the creativity necessary for survival in a constantly changing and volatile business environment. While tradition and conventional wisdom tell us that a middle managers role centers on control and monitoring, todays competitive arena has spun out a new managerial requirement developing and maintaining an innovative attitude. Problematically, most previous research has focused on the issue of changing decision authority (i. e. centralization/decentralization). Moreover, much previous research has also largely ignored environmental changes exposing new roles that middle managers have assumed. This study explores the means of identifying middle managerial roles, managerial possibilities involving the growing popularity of open systems through electronic brainstorming, and an adaptation and development of Diffusion Theory and attempt to counter criticism leveled at the theory's inability to provide an adequate explanation for diffusion of complex organizational technology. This paper develops three ideas: 1) Introducing the 'Chasing Curve' as a theoretical background. 2) Suggesting a new methodology using electronic brainstorming for analyzing the gap between Knowing (the perceived importance of middle managers' roles) and Doing (the degree of current status of middle managers' roles), which we term the 'Spiral Gap Analysis Model'. 3) Identifying a feedback system for minimizing the Knowing - Doing gap, aimed at development of IT strategic priority decision support, which we call this the 'Star Process'.

Special structure of flow networks can reduce the order of the relative existent algorithms. In this paper a special structure of flow network called self-similar f1ow networks is introduced, After describing such networks an efficient algorithm for finding maximum flow is presented. It is shown that this algorithm runs in O(m) time.

In this Paper, an attempt is made to establish a learning framework for robust planning and real-time execution control. Necessary definitions and concepts are clearly presented to describe real-time operational control in response to Plan disruptions. A general mathematical framework for disruption recovery is also laid out. Global disruption model is decomposed into suitable number of local disruption models. Execution Pattern is designed to capture local disruptions using decomposed-reverse neural mappings, and to further demonstrate how the decomposed-reverse mappings could be applied for solving disrubtion recovery problems. Two decomposed-reverse neural mappings, N-K-M and M-K-N are employed to produce transportation solutions in react-time. A potential extension is also discussed using the proposed mapping principle and other hybrid heuristics. Experimental results are provided to verify the proposed approach.