This paper studies a version of the fixed-charge multicommodity network design problem where in addition to the traditional costs of flow and design, congestion at nodes is explicitly considered. The problem is initially modeled as a nonlinear integer programming formulation and two solution approaches are proposed: (i) a reformulation of the problem as a mixed integer second order cone program to optimally solve the problem for small to medium scale problem instances, and (ii) an evolutionary algorithm using elements of iterated local search and scatter search to provide upper bounds. Extensive computational results on new benchmark problem instances and on real case data are presented.
|Number of pages||22|
|Journal||Transportation Research Part E: Logistics and Transportation Review|
|Early online date||17 Dec 2015|
|Publication status||Published - 1 Jan 2016|
- Multi-commodity network design
- evolutionary algorithms