Showing papers on "Network theory published in 1995"

The State and Transnational Corporations: A Network Approach to Industrial Policy in India

Abstract: Strategies in government-TNC networks the transorganizational network theory main objectives and strategic issues operational characteristics of the government-TNC network the political and administrative organization of the government network control of the GTN by the group network implications for network strategies.

Using knowledge about the road network for route finding

Abstract: Imagine a tourist rents a car and plans to drive around a city. Before going from one place to another, he/she needs to know a good way. In network theory, this is the shortest path problem. Shortest path algorithms are often used to solve the problem. However, these algorithms are wasteful in terms of computation when applied to the route finding task. They may also produce solutions that are not appropriate for human drivers. In practice, knowledge about the road network can often be used to substantially reduce the time and space required in computation, and to produce solutions that are suitable for human users. In this project, we have explored the approach of combining a shortest path algorithm with knowledge about the road network to solve the problem. A system (called KB-RFinder) based on this approach has been implemented for route finding in Singapore. >

A business view of networks

Abstract: It goes without saying that graph theory plays a big role in EDA. While we take this for granted in engineering EDA solutions, the business world, EDA and otherwise, has not, for the most part, considered the firm as part of a network. However, especially in high technology, the network form of business organization is an integral part of the business model. This article discusses the network view of business in the EDA context with the following caveats: 1) The author introduces business models but not discusses them in detail; and 2) the underlying management theory on networks draws very little from the mathematics of graph or network theory. >

Nonblocking properties of interconnection switching networks

Abstract: Self-routing interconnection networks with their low processing-overhead delay and decentralized routing, are an attractive option for switching fabrics in high speed networks. These interconnection networks, however, realize only a subset of all possible input-output permutations in a non-blocking fashion. The non-blocking property of these networks is an extensively studied area in interconnection network theory field and efficient algorithms exist to check if any given permutation is passable by such networks without blocking. One of the most common interconnection network structures is the inverse omega network and is topologically equivalent to the reverse banyan network. The authors show how to check the passability by the inverse omega network of any given connection set and list some of the very general patterns passable by this network. They also show that the concentrate operation passable by the inverse omega network is just a special case of the more general alternate sequence operation that they show as being passable. These non-blocking properties will be useful for cell routing in switches built with blocking networks in parallel or in cascade. >

Chapter 6 Probabilistic networks and network algorithms

Abstract: Publisher Summary This chapter discusses probabilistic networks and network algorithms. Probability enters into the theory of networks and network algorithms in several different ways. The most direct way is through probabilistic modeling of some aspect of the network. For example, in some freight management models the cost of transportation along the arcs of the network are modeled by random variables. In models such as these probability helps us grasp a little better a world that comes with its own physical randomness. A second important way probability enters is through more stylized stochastic models where the aim is to provide deeper insight into our technical understanding of the methods of operations research. Here there is considerably less emphasis on building detailed models that hope to capture aspects of randomness that live in a specific application context; rather, the aim is to provide mathematically tractable models of reasonable generality that can be used to explore a variety of different computational or estimation methods. Among the types of issues that have been studied in such models are the efficacies of deterministic algorithms and of deterministic heuristic methods. Many of the 'average case' analyses of algorithms would fit into this second role for probability. The third path by which probability enters into network theory is through randomized algorithms. This is the newest of the roles for probability, but it is a role that is of increasing importance. To make certain of the distinction that makes an algorithm 'randomized,' consider a version of depth-first search where one chooses the next vertex to be explored by selecting it at random from a set of candidates.