An activity-based approach for optimisation of land use and transportation network development

Meng Xu, Hing Keung William Lam, Ziyou Gao, Susan Grant-Muller

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)


This paper tentatively makes use of an activity-based approach to investigate the optimisation problem of land use allocation and transportation network enhancement, in which the budget for investment and some other constraints are given for the purpose of sustainable urban development. To make investigation on residential and employment development as well as road link capacity expansions for short-term strategic planning purposes, a new bi-level programming model is proposed to capture the interactions between land use and transportation network development together with their impacts on activity-travel choice behaviours. The lower level of the proposed model is used to model the choice behaviour of commuters on activity chain, departure time, path and activity scheduling duration simultaneously over the time of day, while the upper level is to maximise the population allocation and network enhancement subject to a set of given constraints. A heuristic solution method is developed to solve the proposed bi-level model. Finally, two numerical examples are presented to demonstrate the application of the proposed model and solution algorithm together with some insightful findings.
Original languageEnglish
Pages (from-to)111-134
Number of pages24
JournalTransportmetrica B
Issue number2
Publication statusPublished - 3 May 2016


  • activity-based approach
  • bi-level programming model
  • genetic algorithm
  • land use and transportation network optimisation
  • sustainable urban development

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Transportation


Dive into the research topics of 'An activity-based approach for optimisation of land use and transportation network development'. Together they form a unique fingerprint.

Cite this