## Abstract

The focus of this paper is to develop a solution framework to study equilibrium transportation network design problems with multiple objectives that are mutually commensurate. Objective parameterization, or scalarization, forms the core idea of this solution approach, by which a multi-objective problem can be equivalently addressed by tackling a series of single-objective problems. In particular, we develop a parameterization-based heuristic that resembles an iterative divide-and-conquer strategy to locate a Pareto-optimal solution in each divided range of commensurate parameters. Unlike its previous counterparts, the heuristic is capable of asymptotically exhausting the complete Pareto-optimal solution set and identifying parameter ranges that exclude any Pareto-optimal solution. Its algorithmic effectiveness and solution characteristics are justified by a set of numerical examples, from which we also gain additional insights about its solution generation behavior and the tradeoff between the computation cost and solution quality.

Original language | English |
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Pages (from-to) | 727-751 |

Number of pages | 25 |

Journal | Networks and Spatial Economics |

Volume | 11 |

Issue number | 4 |

DOIs | |

Publication status | Published - 2011 Dec 1 |

## All Science Journal Classification (ASJC) codes

- Software
- Computer Networks and Communications
- Artificial Intelligence