Robust Transportation Network Design Under Demand Uncertainty

Abstract

This article addresses the problem of a traffic network design problem (NDP) under demand uncertainty. The origin-destination trip matrices are taken as random variables with known probability distributions. Instead of finding optimal network design solutions for a given future scenario, we are concerned with solutions that are in some sense "good" for a variety of demand realizations. We introduce a definition of robustness accounting for the planner's required degree of robustness. We propose a formulation of the robust network design problem (RNDP) and develop a methodology based on genetic algorithm (GA) to solve the RNDP. The proposed model generates globally near-optimal network design solutions, f, based on the planner's input for robustness. The study makes two important contributions to the network design literature. First, robust network design solutions are significantly different from the deterministic NDPs and not accounting for them could potentially underestimate the network-wide impacts. Second, systematic evaluation of the performance of the model and solution algorithm is conducted on different test networks and budget levels to explore the efficacy of this approach. The results highlight the importance of accounting for robustness in transportation planning and the proposed approach is capable of producing high-quality solutions.

User Equilibrium with Recourse

“…All the data for the Nguyen Dupuis network can be found in Ukkusuri et al (2007). Nguyen-Dupuis network was found to be highly congested with all the links in the network being used at the UE solution obtained from the parameters found in Ukkusuri et al (2007). The acyclic Sioux Falls network is similar to the network used in Marcotte et al (2004) with 24 nodes and 37 links and 9 origin destination pairs.…”

“…The NguyenDupuis network has 4 origin destination pairs, 13 nodes and 19 links. All the data for the Nguyen Dupuis network can be found in Ukkusuri et al (2007). Nguyen-Dupuis network was found to be highly congested with all the links in the network being used at the UE solution obtained from the parameters found in Ukkusuri et al (2007).…”

Spatiotemporal Patterns of Urban Human Mobility

“…Some can be direct approaches such as traffic forecasting [1], activity based modeling [2], and the design of transportation networks [3], while some others require more simplified models of human mobility such as the spreading of viruses and the evolution of epidemics [4,5,6,7,8], measuring human exposure to air pollutants [9], and simulating mobile networks of wireless devices [10]. In order to develop models of human mobility, conventionally, information is extracted from travel surveys [11,12,13,14,15].…”

Robust Optimization Model for a Dynamic Network Design Problem Under Demand Uncertainty

“…Karoonsoontawong and Waller (2007) applied this approach to a CTMbased dynamic NDP with stochastic demands under both the system-optimal and user-optimal conditions. A similar RO model formulation approach was employed by Ukkusuri et al (2007), in which a scenario-based robust NDP with discrete decision variables was tackled by a genetic algorithm. The limitations of scenariobased RO approach are similar to stochastic programming in that we must know the probability of each scenario in advance and it is computationally expensive when there are a large number of scenarios.…”