Networks网络

内容概要

Peter Whittle is Professor Emeritus at the University of Cambridge. From 1973 to 1986 he was Director of the Statistical Laboratory, Cambridge. He is a Fellow of the Royal Society and this is his 11th book.

书籍目录

Acknowledgements  Conventions on notation  Tour d'Horizon  Part Ⅰ: Distributional networks   Simple flows   Continuum formulations   Multi-commodity and destination-specific flows   Variable loading   Concave costs and hierarchical structure   Road networks   Structural optimisation: Michell structures   Computational experience of evolutionary algorithms   Structure design for variable load Part Ⅱ: Artificial neural networks   Models and learning   Some particular nets   Oscillatory operation Part Ⅲ: Processing networks   Queueing networks   Time-sharing processor networks Part Ⅳ: Communication networks   Loss networks: optimisation and robustness   Loss networks: stochastics and self-regulation   Operation of the Internet   Evolving networks and the Worldwide Web Appendix 1: Spatial integrals for the telephone problem Appendix 2: Bandit and tax processes Appendix 3: Random graphs and polymer models  ReferencesIndex

作者简介

Point-to-point vs. hub-and-spoke. Questions of network design are real and involve many billions of dollars. Yet little is known about optimising design - nearly all work concerns optimising flow assuming a given design. This foundational book, first published in 2007, tackles optimisation of network structure itself, deriving comprehensible and realistic design principles. With fixed material cost rates, a natural class of models implies the optimality of direct source-destination connections, but considerations of variable load and environmental intrusion then enforce trunking in the optimal design, producing an arterial or hierarchical net. Its determination requires a continuum formulation, which can however be simplified once a discrete structure begins to emerge. Connections are made with the masterly work of Bendsoe and Sigmund on optimal mechanical structures and also with neural, processing and communication networks, including those of the Internet and the World Wide Web. Technical appendices are provided on random graphs and polymer models and on the Klimov index.

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