E-Book, Englisch, Band 450, 488 Seiten, eBook
Pardalos / Hearn / Hager Network Optimization
Erscheinungsjahr 2012
ISBN: 978-3-642-59179-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, Band 450, 488 Seiten, eBook
Reihe: Lecture Notes in Economics and Mathematical Systems
ISBN: 978-3-642-59179-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.