Decomposition scheme for continuous network design problem with asymmetric user equilibria Ban, Xuegang et al
Series: ; 1964Publication details: Transportation research record, 2006Description: s. 185-92Subject(s): Bibl.nr: VTI P8167:1964Location: Abstract: The continuous network design problem is formulated as a mathematical program with complementarity constraints (MPCC) and a Gauss- Seidel decomposition scheme is presented for the solution of the MPCC model. The model has an upper level as a nonlinear programming problem and the lower level as a nonlinear complementarity problem. With the application of the complementarity slackness condition of the lower-level problem, the original bilevel formulation can be converted into a single-level nonlinear programming problem. To solve the single-level problem, a decomposition scheme that can resolve the possible dimensionality problem (i.e., a large number of defining variables) is developed. The decomposition scheme is tested, and promising results are shown for well-known test problems.| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Statens väg- och transportforskningsinstitut | Available |
The continuous network design problem is formulated as a mathematical program with complementarity constraints (MPCC) and a Gauss- Seidel decomposition scheme is presented for the solution of the MPCC model. The model has an upper level as a nonlinear programming problem and the lower level as a nonlinear complementarity problem. With the application of the complementarity slackness condition of the lower-level problem, the original bilevel formulation can be converted into a single-level nonlinear programming problem. To solve the single-level problem, a decomposition scheme that can resolve the possible dimensionality problem (i.e., a large number of defining variables) is developed. The decomposition scheme is tested, and promising results are shown for well-known test problems.