Multi-Objective Decision Method for Airport Landside Rapid Transit Network Design

Area of Science:

• Operations Research
• Transportation Engineering
• Urban Planning

Background:

• Large airports require efficient landside rapid transit networks.
• Current network designs often struggle to balance competing objectives like coverage, travel time, and cost.

Purpose of the Study:

• To develop a multi-objective model for designing airport landside rapid transit networks.
• To optimize passenger demand coverage, reduce travel time, and minimize operational costs simultaneously.

Main Methods:

• Formulation of an integer programming problem for network design.
• Application of a branch-and-cut algorithm to identify non-inferior solutions.
• Trade-off analysis using the modified Gini coefficient to assess efficiency, effectiveness, and equity.

Main Results:

• The star topology demonstrated superior cost-effectiveness for passenger demand coverage and travel time reduction.
• Finger topology achieved the highest passenger demand coverage and travel time reduction but incurred the highest costs.
• Maximizing passenger demand coverage led to higher efficiency and lower unit costs compared to minimizing travel time, which offered greater equity.

Conclusions:

• The proposed multi-objective model and algorithm effectively support airport transit network design.
• Network topology significantly impacts performance metrics; star topology is cost-efficient, while finger topology maximizes service but at a higher cost.
• Decision-makers can leverage this approach to balance competing objectives and improve airport landside transit service levels.