.png){kind=icon}
Return
A spatial knowledge-driven decision support framework for multi-objective bus corridor design: a simulation-optimization approach
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2026.132957.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Rapid urbanization has transformed bus corridor planning into a complex network-scale decision problem that requires balancing transit efficiency, land-use heterogeneity, investment feasibility, and congestion redistribution. However, existing approaches are often limited by static evaluation and weak representation of land-use conditions. To address these limitations, this study develops a spatial knowledge-driven Simulation-Optimization framework for multi-objective bus corridor design. Central to this framework is a Corridor Development Potential Index derived from point-of-interest data, which quantifies service density, functional diversity, and accessibility at the link level. This spatial knowledge is integrated with travel efficiency and construction cost in a multi-objective corridor optimization model, governed by explicit physical continuity and feasibility constraints. To ensure behavioural realism, the optimization process is coupled iteratively with traffic assignment equilibrium, allowing corridor configurations to evolve according to feedback on network performance. Application to the Chongqing metropolitan network demonstrates that the framework produces spatially coherent and operationally viable schemes. Scenario analyses reveal a policy-dependent spatial logic: cost-oriented configurations favour incremental upgrades in the urban core; development-oriented strategies facilitate expansion into emerging growth poles; and efficiency-oriented designs reinforce continuous arterial backbones. In total, these findings highlight the framework's computational efficiency and its practical utility as a strategic decisionsupport tool for large-scale urban infrastructure planning.
Keywords:
Simulation-optimization
Bus corridor design
Multi-objective optimization
Point-of-Interest data
Decision support framework
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
Organization
Cited Papers
No cited papers available