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For urban planning, transportation system in a region is essentially a result of the activity participation among geographically distributed locations. Facing congestion, pollution and other serious challenges, Metropolitan Planning Organizations (MPOs) need to offer effective decision-making supports to urban planning, especially urban layout optimization solutions. By mathematically defining the urban layout problem as a joint optimization of (a) activity space (AS)-to-location assignment, (b) demand distribution and (c) traffic flow assignment, this paper constructs an urban layout model by extending the quadratic assignment problem (QAP). In comparison with the standard model, our proposed framework considers possible flow distribution between different types of urban amenities, subject to the region-level demand control total constraint for certain activity types. A Maximal AS-to-location flow (MaxASLF) based heuristic algorithm and a Lagrangian relaxation-based approach are designed to solve the proposed models. Various examples and discussions are provided to examine the effectiveness of the proposed methods.

Robust gate assignment problem (RGAP) aims to generate a reliable schedule that reduces the occurrence of potential gate conflicts under stochastic flight delays. Although allocating buffer time in the gate schedules is widely adopted to absorb the delay disturbances, the relation between the schedule robustness and the aircraft delay heterogeneity has not yet been well explored. To allocate the buffer optimally, we analyse the heterogeneity of gate conflict and propose two new robustness measurements to quantify the number of potential conflicts from the expectation perspective. Then the RGAP is modelled as a set-covering problem to simultaneously optimise the expected conflict cost and basic operating cost. To solve the model efficiently, we develop a column generation-based heuristic (CDBH) to find high-quality solutions. Computational studies based on Shenzhen Baoan International Airport reveal that the proposed measurements considering the delay heterogeneity can significantly improve the robustness of gate schedules.

The integrated aviation and High-Speed Railway (HSR) transportation system plays a vital role for today’s inter-city transportation services. However, an increasing number of unexpected disruptions (such as operation failures, natural disasters, or intentional attacks) pose a considerable threat to the normal operation of the system, especially on ground transfer, leading to the extensive research on its vulnerability. Previous approaches mainly focus on interruptions within a single transportation mode, neglecting the role of ground transfer which serves as a coupled connection between aviation and High-Speed Railway. This paper proposes a network-based framework for evaluating the vulnerability of the Chinese Coupled Aviation and High-Speed Railway (CAHSR) network from the viewpoint of ground transfer interruption. Taking the end-to-end travel time and passenger flow information into consideration as an evaluation measure and analyzing from the perspective of urban agglomerations, an adaptive method is developed to identify the critical cities and further investigate their failure impacts on the geographic distribution of vulnerability. In addition, the proposed model explores variations of vulnerability under different failure time intervals. Based on the empirical study, some major conclusions are highlighted as follows: (A) Only a few cities show significant impacts on the network’s vulnerability when ground transfer interruptions occurred. (B) The distribution of vulnerability is not proportional to the distance between failure city and influenced city. (C) The vulnerability is more serious in the morning and evening when the ground transfer is disconnected. Our findings may provide new insights for maintenance and optimization of the CAHSR network and other real-world transportation networks.