An integrated design of sustainable land use and transportation system with uncertainty in future population

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.

Keywords:

• integration of land use and transportation
• sustainability
• population uncertainty
• two-stage robust design
• chance constraint
• simulated annealing method

Acknowledgements

The research work of this article was mainly carried out when the first and second authors visited the Hong Kong Polytechnic University in 2010. The work described in this article was jointly supported by grants from the Faculty of Construction and Environment of the Hong Kong Polytechnic University (1-ZV4T), the Research Committee of the Hong Kong Polytechnic University (G-YX1V), the National Natural Science Foundation of China (71171013, 70971045, 71222107), the Research Foundation for the Author of National Excellent Doctoral Dissertation (China) (200963), the Fok Ying Tung Education Foundation (132015) and the Center for Modern Information Management Research at the Huazhong University of Science & Technology.