A survey of some mathematical programming models in transportation
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Publication:1367685
DOI10.1007/BF02568528zbMath0887.90054OpenAlexW2056452679MaRDI QIDQ1367685
Publication date: 6 May 1998
Published in: Top (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf02568528
Programming involving graphs or networks (90C35) Applications of mathematical programming (90C90) Transportation, logistics and supply chain management (90B06) Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming (90-02)
Related Items (5)
A column generation algorithm for the estimation of origin-destination matrices in congested traffic networks ⋮ Approximation of the steepest descent direction for the O-D matrix adjustment problem ⋮ New algorithmic alternatives for the O--D matrix adjustment problem on traffic networks ⋮ Adjustment of O-D trip matrices from observed volumes: an algorithmic approach based on conjugate directions. ⋮ Simultaneous estimation of the origin-destination matrices and the parameters of a nested logit model in a combined network equilibrium model
Uses Software
Cites Work
- Convex two-level optimization
- A simplicial decomposition algorithm for solving the variational inequality formulation of the general traffic assignment problem for large scale network
- On the convergence of descent methods for monotone variational inequalities
- Modéles De Distribution Spatiale Tenant Compte Des ItinéRaires
- Optimization and nonsmooth analysis
- Nonlinear cost network models in transportation analysis
- Restricted simplicial decomposition: Computation and extensions
- An efficient implementation of the “partan” variant of the linear approximation method for the network equilibrium problem
- Sensitivity Analysis for Equilibrium Network Flow
- Projection methods for variational inequalities with application to the traffic assignment problem
- Simplicial Decomposition with Disaggregated Representation for the Traffic Assignment Problem
- Simplicial decomposition in nonlinear programming algorithms
- Projected Newton Methods for Optimization Problems with Simple Constraints
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