Network optimization is important in the modeling of problems and processes from such fields as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Recent advances in data structures, computer technology, and algorithm development have made it possible to solve classes of network optimization problems that until recently were intractable. The refereed papers in this volume reflect the interdisciplinary efforts of a large group of scientists from academia and industry to model and solve complicated large-scale network optimization problems.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
A Pavement Network Optimization System Using Dantzig-Wolfe Decomposition.- Integer Multicommodity Flow Problems.- Solution Methods for Nonconvex Network Flow Problems.- Congestion Toll Pricing of Traffic Networks.- Solving the Nonadditive Traffic Equilibrium Problem.- ?-Relaxation and Auction Methods for Separable Convex Cost Network Flow Problems.- A Communication Assignment Problem on Trees: Heuristics and Asymptotic behavior.- The Inverse Shortest Paths Problem with Upper Bounds on Shortest Paths Costs.- Distributed Disaggregate Simplicial Decomposition ? A Parallel Algorithm for Traffic Assignment.- Computation of Constrained Spanning Trees: A Unified Approach.- Two Special Cases for Rectilinear Steiner Minimum Trees.- Decomposition Methods for Network Optimization Problems in the Presence of Uncertainty.- Network Methods for Head-dependent Hydro Power Scheduling.- An Efficient Implementation of the Network Simplex Method.- Implementations of Dijkstra’s Algorithm Based on Multi-Level Buckets.- NET SPEAK: An Algebraic Modelling Language for Nonconvex Network Optimization Problems.- Applications of Simplicial Decomposition with Nonlinear Column Generations to Nonlinear Network Flows.- Massively Parallel Computation of Dynamic Traffic Networks Modeled as Projected Dynamical Systems.- Solving the Survivable Network Design Problem with Search Space Smoothing.- Track Initiation and Maintenance Using Multidimensional Assignment Problems.- An Optimal Control Formulation of Large-Scale Multiclass Machine Scheduling Problems.- Interior Point Methods for Supervised Training of Artificial Neural Networks with Bounded Weights.- Approximate Lagrangian Decomposition with a Modified Karmarkar Logarithmic Potential.
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