This is a book about infrastructure networks that are intrinsically nonlinear. The networks considered range from vehicular networks to electric power networks to data networks.

The main point of view taken is that of mathematical programming in concert with finite-dimensional variational inequality theory. The principle modeling perspectives are network optimization, the theory of Nash games, and mathematical programming with equilibrium constraints. Computational methods and novel mathematical formulations are emphasized. Among the numerical methods explored are network simplex, gradient projection, fixed-point, gap function, Lagrangian relaxation, Dantzig-Wolfe decomposition, simplicial decomposition, and computational intelligence algorithms.

Many solved example problems are included that range from simple to quite challenging. Theoretical analyses of several models and algorithms, to uncover existence, uniqueness and convergence properties, are undertaken. The bookis meant for use in advanced undergraduate as well as doctoral courses taught in civil engineering, industrial engineering, systems engineering, and operations research degree programs. At the same time, the book should be a useful resource for industrial and university researchers engaged in the mathematical modeling and numerical analyses of infrastructure networks.

For practitioners, researchers, and advanced students in Civil Engineering, Industrial Engineering, Systems Engineering, and Operations Research Useful reference for researchers in the design and operation of transportation, water resource, telecommunication, and energy infrastructure Presents many numerical examples throughout

Inhalt

Introduction.- Elements of Nonlinear Programming.- Elements of Graph Theory.- Programs with Network Structure.- Near-Network and Large-Scale Programs.- Normative Network Models and Their Solution.- Nash Games.- Network Traffic Assignment.- Spatial Price Equilibrium on Networks.- Network Stackelberg Games and Mathematical Programs with Equilibrium Constraints.