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Title: An integrated design of sustainable land use and transportation system with uncertainty in future population
Authors: Li, ZC
Li, ZK
Lam, WHK 
Keywords: Chance constraint
Integration of land use and transportation
Population uncertainty
Simulated annealing method
Two-stage robust design
Issue Date: 2014
Publisher: Taylor & Francis
Source: Transportmetrica. A, Transport science, 2014, v. 10, no. 2, p. 160-185 How to cite?
Journal: Transportmetrica. A, Transport science 
Abstract: This article proposes a new model for integrated design of a sustainable land use and transportation system with uncertainty in future population. In the proposed model, the future population in the urban area is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to road capacity expansion, housing and employment supplies and environmental impacts is incorporated to consider the sustainability of urban land development and transportation infrastructure improvement. The proposed model is formulated as a two-stage robust optimisation problem. The first stage of the proposed model (before the future urban population is realised) is to optimise the land use and transportation system by maximising a robust risk-averse objective function subject to various chance constraints for consideration of the system sustainability. The second stage of the proposed model, after the future population has been determined, is a scenario-based stochastic location and route choice equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, simulated annealing method and Gauss-Seidel decomposition approach is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that the integrated design of the sustainable land use and transportation system depends very much on the level of uncertainty in future population, capital budget for urban development, and confidence levels of the chance constraints.
ISSN: 2324-9935
EISSN: 2324-9943
DOI: 10.1080/18128602.2012.725268
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