01128837

Component

https://doi.org/10.3141/2090-11

http://scholar.google.com...thew&publication_year=2009

A study was done to formulate and solve the multiobjective network design problem with uncertain demand. Various samples of demand are realized for optimal improvements in the network while the objectives of the expected total system travel time and the higher moment for total system travel time are minimized. A formulation is proposed for multiobjective robust network design, and a solution methodology is developed on the basis of a revised fast and elitist nondominated sorting genetic algorithm. The developed methodology has been tested on the Nguyen–Dupuis network, and various Pareto optimal solutions are compared with earlier work on the single-objective robust network design problem. A real medium-size network was solved to prove efficacy of the model. The results show better solutions for the multiobjective robust network design problem with relatively less computational effort.

01135938

09-2257

English

pp 95-104

2009

Transportation Research Record: Journal of the Transportation Research Board

9780309126090

Print

Figures (5) ; References (35) ; Tables (3)

Genetic algorithms; Travel demand; Travel time

Multiobjective optimization; Network design problem; Pareto optimum

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 30 2009 6:36PM

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• Calibration of Dynamic Traffic Assignment Models with Point-to-Point Traffic Surveillance
• Dynamic Pricing with Heterogeneous Users: Gap-Driven Solution Approach for Bicriterion Dynamic User Equilibrium Problem
• Evaluation and Design of Transport Network Capacity Under Demand Uncertainty
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• Measuring Network Reliability Considering Paradoxes: Multiple Network Demon Approach
• Multimodal Mesoscopic Approach in Modeling Pedestrian Evacuation
• Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits
• Reliable System-Optimal Network Design: Convex Mean–Variance Model with Implicit Chance Constraints
• Robust Approach to Discrete Network Designs with Demand Uncertainty